First Results: Skill Building and Self-Acceptance as Mechanisms of Positive Personality Change
Author
Michael Krämer
1 Load packages
Show the code
library(renv)library(tidyverse)library(broom)library(labelled)library(psych)library(GPArotation)#library(devtools)#install_github("cran/multicon") # not on CRAN atmlibrary(multicon)library(correlation)library(corrplot)library(lavaan)library(semTools)library(semPlot)library(knitr)library(ggdist)library(ggforce)library(nortest)
All four psychological well-being indicators will be positively correlated with a greater similarity between current- and ideal self-ratings of personality.
To examine this at the level of overall profiles, we will compute the correlations between the psychological well-being indicators and the Fisher z transformed correlations between the facet- and item-level real-ideal self-profiles. To examine this at the level of individual traits, we will compute the correlation between psychological well-being indicators and the squared difference between current- and ideal-self rating for each Big Five trait and facet.
corrplot(cormat_profile, type ="lower", order ="original", tl.col ="black", tl.srt =10,addCoef.col ='black', number.cex =0.7, diag =FALSE) # also add numbers
Positive correlations of well-being indicators with profile similarity between current self and ideal self personality. Especially high correlation with self-esteem. High congruence of item-level and facet-level profile similarity.
corrplot(cormat_sqtraits, type ="lower", order ="original", tl.col ="black", tl.srt =10,addCoef.col ='black', number.cex =0.7, diag =FALSE) # also add numbers
Big Five facets
corrplot(cormat_sqfacets, type ="lower", order ="original", tl.col ="black", tl.srt =10,addCoef.col ='black', number.cex =0.6, diag =FALSE) # also add numbers
Here we see negative correlations of well-being indicators with squared trait- and facet-level mean-score differences between current self and ideal self personality.
3.2 Measurement invariance: Well-being indicators
Testing for measurement invariance of the latent traits across time.
Relatively bad model fit across all model specifications. Chi^2 tests indicate that only weak measurement invariance is given.
3.3 Hypothesis 2: Well-being - latent change
Both groups will increase in all four psychological well-being indicators.
We will test the mean-level difference between baseline and follow up using a latent change model.
3.3.1 Life satisfaction
Fit model:
Show the code
# Code snippets adapted from Kievit et al. (2018) -- CC-BY -- https://doi.org/10.1016/j.dcn.2017.11.007# Fit the multiple indicator Univariate Latent Change Score modelmi_lcs_swls_hyp2 <-'swls_t1 =~ 1*sw06_01_t1 + lamb2*sw06_02_t1 + lamb3*sw06_03_t1 + lamb4*sw06_04_t1 + lamb5*sw06_05_t1 # This specifies the measurement model for swls_t1 swls_t2 =~ 1*sw06_01_t2 + lamb2*sw06_02_t2 + lamb3*sw06_03_t2 + lamb4*sw06_04_t2 + lamb5*sw06_05_t2 # This specifies the measurement model for swls_t2 with the equality constrained factor loadingsswls_t2 ~ 1*swls_t1 # This parameter regresses swls_t2 perfectly on swls_t1d_swls_1 =~ 1*swls_t2 # This defines the latent change score factor as measured perfectly by scores on swls_t2swls_t2 ~ 0*1 # This line constrains the intercept of swls_t2 to 0swls_t2 ~~ 0*swls_t2 # This fixes the variance of swls_t2 to 0d_swls_1 ~ 1 # This estimates the intercept of the change score swls_t1 ~ 1 # This estimates the intercept of swls_t1 d_swls_1 ~~ d_swls_1 # This estimates the variance of the change scores swls_t1 ~~ swls_t1 # This estimates the variance of the swls_t1 d_swls_1 ~ swls_t1 # This estimates the self-feedback parametersw06_01_t1 ~~ sw06_01_t2 # This allows residual covariance on indicator X1 across T1 and T2sw06_02_t1 ~~ sw06_02_t2 # This allows residual covariance on indicator X2 across T1 and T2sw06_03_t1 ~~ sw06_03_t2 # This allows residual covariance on indicator X3 across T1 and T2sw06_04_t1 ~~ sw06_04_t2 # This allows residual covariance on indicator X4 across T1 and T2sw06_05_t1 ~~ sw06_05_t2 # This allows residual covariance on indicator X5 across T1 and T2sw06_01_t1 ~~ res1*sw06_01_t1 # This allows residual variance on indicator X1 at T1 sw06_02_t1 ~~ res2*sw06_02_t1 # This allows residual variance on indicator X2 at T1sw06_03_t1 ~~ res3*sw06_03_t1 # This allows residual variance on indicator X3 at T1sw06_04_t1 ~~ res4*sw06_04_t1 # This allows residual variance on indicator X4 at T1sw06_05_t1 ~~ res5*sw06_05_t1 # This allows residual variance on indicator X5 at T1sw06_01_t2 ~~ res1*sw06_01_t2 # This allows residual variance on indicator X1 at T2 sw06_02_t2 ~~ res2*sw06_02_t2 # This allows residual variance on indicator X2 at T2 sw06_03_t2 ~~ res3*sw06_03_t2 # This allows residual variance on indicator X3 at T2sw06_04_t2 ~~ res4*sw06_04_t2 # This allows residual variance on indicator X4 at T2sw06_05_t2 ~~ res5*sw06_05_t2 # This allows residual variance on indicator X5 at T2sw06_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1sw06_02_t1 ~ m2*1 # This estimates the intercept of X2 at T1sw06_03_t1 ~ m3*1 # This estimates the intercept of X3 at T1sw06_04_t1 ~ m4*1 # This estimates the intercept of X4 at T1sw06_05_t1 ~ m5*1 # This estimates the intercept of X5 at T1sw06_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2sw06_02_t2 ~ m2*1 # This estimates the intercept of X2 at T2sw06_03_t2 ~ m3*1 # This estimates the intercept of X3 at T2sw06_04_t2 ~ m4*1 # This estimates the intercept of X4 at T2sw06_05_t2 ~ m5*1 # This estimates the intercept of X5 at T2'fit_mi_lcs_swls_hyp2 <-lavaan(mi_lcs_swls_hyp2, data=df_sbsa_wide_wb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_swls_hyp2, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Significantly higher life satisfaction at the post test. Those with initially higher levels of life satisfaction (at T1) change to a lesser degree.
3.3.2 Meaning in life
Fit model:
Show the code
# Code snippets adapted from Kievit et al. (2018) -- CC-BY -- https://doi.org/10.1016/j.dcn.2017.11.007# Fit the multiple indicator Univariate Latent Change Score modelmi_lcs_meaning_hyp2 <-'meaning_t1 =~ 1*ml01_01_t1 + lamb2*ml01_02_t1 + lamb3*ml01_03_t1 + lamb4*ml01_04_t1 + lamb5*ml01_05_t1 + lamb6*ml01_06_t1 + lamb7*ml01_07_t1 + lamb8*ml01_08_t1 + lamb9*ml01_09_t1 + lamb10*ml01_10_t1 # This specifies the measurement model for meaning_t1 meaning_t2 =~ 1*ml01_01_t2 + lamb2*ml01_02_t2 + lamb3*ml01_03_t2 + lamb4*ml01_04_t2 + lamb5*ml01_05_t2 + lamb6*ml01_06_t2 + lamb7*ml01_07_t2 + lamb8*ml01_08_t2 + lamb9*ml01_09_t2 + lamb10*ml01_10_t2 # This specifies the measurement model for meaning_t2 with the equality constrained factor loadingsmeaning_t2 ~ 1*meaning_t1 # This parameter regresses meaning_t2 perfectly on meaning_t1d_meaning_1 =~ 1*meaning_t2 # This defines the latent change score factor as measured perfectly by scores on meaning_t2meaning_t2 ~ 0*1 # This line constrains the intercept of meaning_t2 to 0meaning_t2 ~~ 0*meaning_t2 # This fixes the variance of meaning_t2 to 0d_meaning_1 ~ 1 # This estimates the intercept of the change score meaning_t1 ~ 1 # This estimates the intercept of meaning_t1 d_meaning_1 ~~ d_meaning_1 # This estimates the variance of the change scores meaning_t1 ~~ meaning_t1 # This estimates the variance of the meaning_t1 d_meaning_1 ~ meaning_t1 # This estimates the self-feedback parameterml01_01_t1 ~~ ml01_01_t2 # This allows residual covariance on indicator X1 across T1 and T2ml01_02_t1 ~~ ml01_02_t2 # This allows residual covariance on indicator X2 across T1 and T2ml01_03_t1 ~~ ml01_03_t2 # This allows residual covariance on indicator X3 across T1 and T2ml01_04_t1 ~~ ml01_04_t2 # This allows residual covariance on indicator X4 across T1 and T2ml01_05_t1 ~~ ml01_05_t2 # This allows residual covariance on indicator X5 across T1 and T2ml01_06_t1 ~~ ml01_06_t2 # This allows residual covariance on indicator X6 across T1 and T2ml01_07_t1 ~~ ml01_07_t2 # This allows residual covariance on indicator X7 across T1 and T2ml01_08_t1 ~~ ml01_08_t2 # This allows residual covariance on indicator X8 across T1 and T2ml01_09_t1 ~~ ml01_09_t2 # This allows residual covariance on indicator X9 across T1 and T2ml01_10_t1 ~~ ml01_10_t2 # This allows residual covariance on indicator X10 across T1 and T2ml01_01_t1 ~~ res1*ml01_01_t1 # This allows residual variance on indicator X1 at T1 ml01_02_t1 ~~ res2*ml01_02_t1 # This allows residual variance on indicator X2 at T1ml01_03_t1 ~~ res3*ml01_03_t1 # This allows residual variance on indicator X3 at T1ml01_04_t1 ~~ res4*ml01_04_t1 # This allows residual variance on indicator X4 at T1ml01_05_t1 ~~ res5*ml01_05_t1 # This allows residual variance on indicator X5 at T1ml01_06_t1 ~~ res6*ml01_06_t1 # This allows residual variance on indicator X6 at T1 ml01_07_t1 ~~ res7*ml01_07_t1 # This allows residual variance on indicator X7 at T1ml01_08_t1 ~~ res8*ml01_08_t1 # This allows residual variance on indicator X8 at T1ml01_09_t1 ~~ res9*ml01_09_t1 # This allows residual variance on indicator X9 at T1ml01_10_t1 ~~ res10*ml01_10_t1 # This allows residual variance on indicator X10 at T1ml01_01_t2 ~~ res1*ml01_01_t2 # This allows residual variance on indicator X1 at T2 ml01_02_t2 ~~ res2*ml01_02_t2 # This allows residual variance on indicator X2 at T2 ml01_03_t2 ~~ res3*ml01_03_t2 # This allows residual variance on indicator X3 at T2ml01_04_t2 ~~ res4*ml01_04_t2 # This allows residual variance on indicator X4 at T2ml01_05_t2 ~~ res5*ml01_05_t2 # This allows residual variance on indicator X5 at T2ml01_06_t2 ~~ res6*ml01_06_t2 # This allows residual variance on indicator X6 at T2 ml01_07_t2 ~~ res7*ml01_07_t2 # This allows residual variance on indicator X7 at T2 ml01_08_t2 ~~ res8*ml01_08_t2 # This allows residual variance on indicator X8 at T2ml01_09_t2 ~~ res9*ml01_09_t2 # This allows residual variance on indicator X9 at T2ml01_10_t2 ~~ res10*ml01_10_t2 # This allows residual variance on indicator X10 at T2ml01_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ml01_02_t1 ~ m2*1 # This estimates the intercept of X2 at T1ml01_03_t1 ~ m3*1 # This estimates the intercept of X3 at T1ml01_04_t1 ~ m4*1 # This estimates the intercept of X4 at T1ml01_05_t1 ~ m5*1 # This estimates the intercept of X5 at T1ml01_06_t1 ~ m6*1 # This estimates the intercept of X6 at T1ml01_07_t1 ~ m7*1 # This estimates the intercept of X7 at T1ml01_08_t1 ~ m8*1 # This estimates the intercept of X8 at T1ml01_09_t1 ~ m9*1 # This estimates the intercept of X9 at T1ml01_10_t1 ~ m10*1 # This estimates the intercept of X10 at T1ml01_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ml01_02_t2 ~ m2*1 # This estimates the intercept of X2 at T2ml01_03_t2 ~ m3*1 # This estimates the intercept of X3 at T2ml01_04_t2 ~ m4*1 # This estimates the intercept of X4 at T2ml01_05_t2 ~ m5*1 # This estimates the intercept of X5 at T2ml01_06_t2 ~ m6*1 # This estimates the intercept of X6 at T2ml01_07_t2 ~ m7*1 # This estimates the intercept of X7 at T2ml01_08_t2 ~ m8*1 # This estimates the intercept of X8 at T2ml01_09_t2 ~ m9*1 # This estimates the intercept of X9 at T2ml01_10_t2 ~ m10*1 # This estimates the intercept of X10 at T2'fit_mi_lcs_meaning_hyp2 <-lavaan(mi_lcs_meaning_hyp2, data=df_sbsa_wide_wb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_meaning_hyp2, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Very bad model fit… Participants improved significantly in meaning in life across time.
3.3.3 Self-esteem
Fit model:
Show the code
# Code snippets adapted from Kievit et al. (2018) -- CC-BY -- https://doi.org/10.1016/j.dcn.2017.11.007# Fit the multiple indicator Univariate Latent Change Score modelmi_lcs_selfes_hyp2 <-'selfes_t1 =~ 1*rs01_01_t1 + lamb2*rs01_02_t1 + lamb3*rs01_03_t1 + lamb4*rs01_04_t1 + lamb5*rs01_05_t1 + lamb6*rs01_06_t1 + lamb7*rs01_07_t1 + lamb8*rs01_08_t1 + lamb9*rs01_09_t1 + lamb10*rs01_10_t1 # This specifies the measurement model for selfes_t1 selfes_t2 =~ 1*rs01_01_t2 + lamb2*rs01_02_t2 + lamb3*rs01_03_t2 + lamb4*rs01_04_t2 + lamb5*rs01_05_t2 + lamb6*rs01_06_t2 + lamb7*rs01_07_t2 + lamb8*rs01_08_t2 + lamb9*rs01_09_t2 + lamb10*rs01_10_t2 # This specifies the measurement model for selfes_t2 with the equality constrained factor loadingsselfes_t2 ~ 1*selfes_t1 # This parameter regresses selfes_t2 perfectly on selfes_t1d_selfes_1 =~ 1*selfes_t2 # This defines the latent change score factor as measured perfectly by scores on selfes_t2selfes_t2 ~ 0*1 # This line constrains the intercept of selfes_t2 to 0selfes_t2 ~~ 0*selfes_t2 # This fixes the variance of selfes_t2 to 0d_selfes_1 ~ 1 # This estimates the intercept of the change score selfes_t1 ~ 1 # This estimates the intercept of selfes_t1 d_selfes_1 ~~ d_selfes_1 # This estimates the variance of the change scores selfes_t1 ~~ selfes_t1 # This estimates the variance of the selfes_t1 d_selfes_1 ~ selfes_t1 # This estimates the self-feedback parameterrs01_01_t1 ~~ rs01_01_t2 # This allows residual covariance on indicator X1 across T1 and T2rs01_02_t1 ~~ rs01_02_t2 # This allows residual covariance on indicator X2 across T1 and T2rs01_03_t1 ~~ rs01_03_t2 # This allows residual covariance on indicator X3 across T1 and T2rs01_04_t1 ~~ rs01_04_t2 # This allows residual covariance on indicator X4 across T1 and T2rs01_05_t1 ~~ rs01_05_t2 # This allows residual covariance on indicator X5 across T1 and T2rs01_06_t1 ~~ rs01_06_t2 # This allows residual covariance on indicator X6 across T1 and T2rs01_07_t1 ~~ rs01_07_t2 # This allows residual covariance on indicator X7 across T1 and T2rs01_08_t1 ~~ rs01_08_t2 # This allows residual covariance on indicator X8 across T1 and T2rs01_09_t1 ~~ rs01_09_t2 # This allows residual covariance on indicator X9 across T1 and T2rs01_10_t1 ~~ rs01_10_t2 # This allows residual covariance on indicator X10 across T1 and T2rs01_01_t1 ~~ res1*rs01_01_t1 # This allows residual variance on indicator X1 at T1 rs01_02_t1 ~~ res2*rs01_02_t1 # This allows residual variance on indicator X2 at T1rs01_03_t1 ~~ res3*rs01_03_t1 # This allows residual variance on indicator X3 at T1rs01_04_t1 ~~ res4*rs01_04_t1 # This allows residual variance on indicator X4 at T1rs01_05_t1 ~~ res5*rs01_05_t1 # This allows residual variance on indicator X5 at T1rs01_06_t1 ~~ res6*rs01_06_t1 # This allows residual variance on indicator X6 at T1 rs01_07_t1 ~~ res7*rs01_07_t1 # This allows residual variance on indicator X7 at T1rs01_08_t1 ~~ res8*rs01_08_t1 # This allows residual variance on indicator X8 at T1rs01_09_t1 ~~ res9*rs01_09_t1 # This allows residual variance on indicator X9 at T1rs01_10_t1 ~~ res10*rs01_10_t1 # This allows residual variance on indicator X10 at T1rs01_01_t2 ~~ res1*rs01_01_t2 # This allows residual variance on indicator X1 at T2 rs01_02_t2 ~~ res2*rs01_02_t2 # This allows residual variance on indicator X2 at T2 rs01_03_t2 ~~ res3*rs01_03_t2 # This allows residual variance on indicator X3 at T2rs01_04_t2 ~~ res4*rs01_04_t2 # This allows residual variance on indicator X4 at T2rs01_05_t2 ~~ res5*rs01_05_t2 # This allows residual variance on indicator X5 at T2rs01_06_t2 ~~ res6*rs01_06_t2 # This allows residual variance on indicator X6 at T2 rs01_07_t2 ~~ res7*rs01_07_t2 # This allows residual variance on indicator X7 at T2 rs01_08_t2 ~~ res8*rs01_08_t2 # This allows residual variance on indicator X8 at T2rs01_09_t2 ~~ res9*rs01_09_t2 # This allows residual variance on indicator X9 at T2rs01_10_t2 ~~ res10*rs01_10_t2 # This allows residual variance on indicator X10 at T2rs01_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1rs01_02_t1 ~ m2*1 # This estimates the intercept of X2 at T1rs01_03_t1 ~ m3*1 # This estimates the intercept of X3 at T1rs01_04_t1 ~ m4*1 # This estimates the intercept of X4 at T1rs01_05_t1 ~ m5*1 # This estimates the intercept of X5 at T1rs01_06_t1 ~ m6*1 # This estimates the intercept of X6 at T1rs01_07_t1 ~ m7*1 # This estimates the intercept of X7 at T1rs01_08_t1 ~ m8*1 # This estimates the intercept of X8 at T1rs01_09_t1 ~ m9*1 # This estimates the intercept of X9 at T1rs01_10_t1 ~ m10*1 # This estimates the intercept of X10 at T1rs01_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2rs01_02_t2 ~ m2*1 # This estimates the intercept of X2 at T2rs01_03_t2 ~ m3*1 # This estimates the intercept of X3 at T2rs01_04_t2 ~ m4*1 # This estimates the intercept of X4 at T2rs01_05_t2 ~ m5*1 # This estimates the intercept of X5 at T2rs01_06_t2 ~ m6*1 # This estimates the intercept of X6 at T2rs01_07_t2 ~ m7*1 # This estimates the intercept of X7 at T2rs01_08_t2 ~ m8*1 # This estimates the intercept of X8 at T2rs01_09_t2 ~ m9*1 # This estimates the intercept of X9 at T2rs01_10_t2 ~ m10*1 # This estimates the intercept of X10 at T2'fit_mi_lcs_selfes_hyp2 <-lavaan(mi_lcs_selfes_hyp2, data=df_sbsa_wide_wb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_selfes_hyp2, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Participants increased significantly in self-esteem between the two assessments.
3.3.4 Self concept clarity
Fit model:
Show the code
# Code snippets adapted from Kievit et al. (2018) -- CC-BY -- https://doi.org/10.1016/j.dcn.2017.11.007# Fit the multiple indicator Univariate Latent Change Score modelmi_lcs_concept_hyp2 <-'concept_t1 =~ 1*sc01_01_t1 + lamb2*sc01_02_t1 + lamb3*sc01_03_t1 + lamb4*sc01_04_t1 + lamb5*sc01_05_t1 + lamb6*sc01_06_t1 + lamb7*sc01_07_t1 + lamb8*sc01_08_t1 + lamb9*sc01_09_t1 + lamb10*sc01_10_t1 + lamb11*sc01_11_t1 + lamb12*sc01_12_t1 # This specifies the measurement model for concept_t1 concept_t2 =~ 1*sc01_01_t2 + lamb2*sc01_02_t2 + lamb3*sc01_03_t2 + lamb4*sc01_04_t2 + lamb5*sc01_05_t2 + lamb6*sc01_06_t2 + lamb7*sc01_07_t2 + lamb8*sc01_08_t2 + lamb9*sc01_09_t2 + lamb10*sc01_10_t2 + lamb11*sc01_11_t2 + lamb12*sc01_12_t2 # This specifies the measurement model for concept_t2 with the equality constrained factor loadingsconcept_t2 ~ 1*concept_t1 # This parameter regresses concept_t2 perfectly on concept_t1d_concept_1 =~ 1*concept_t2 # This defines the latent change score factor as measured perfectly by scores on concept_t2concept_t2 ~ 0*1 # This line constrains the intercept of concept_t2 to 0concept_t2 ~~ 0*concept_t2 # This fixes the variance of concept_t2 to 0d_concept_1 ~ 1 # This estimates the intercept of the change score concept_t1 ~ 1 # This estimates the intercept of concept_t1 d_concept_1 ~~ d_concept_1 # This estimates the variance of the change scores concept_t1 ~~ concept_t1 # This estimates the variance of the concept_t1 d_concept_1 ~ concept_t1 # This estimates the self-feedback parametersc01_01_t1 ~~ sc01_01_t2 # This allows residual covariance on indicator X1 across T1 and T2sc01_02_t1 ~~ sc01_02_t2 # This allows residual covariance on indicator X2 across T1 and T2sc01_03_t1 ~~ sc01_03_t2 # This allows residual covariance on indicator X3 across T1 and T2sc01_04_t1 ~~ sc01_04_t2 # This allows residual covariance on indicator X4 across T1 and T2sc01_05_t1 ~~ sc01_05_t2 # This allows residual covariance on indicator X5 across T1 and T2sc01_06_t1 ~~ sc01_06_t2 # This allows residual covariance on indicator X6 across T1 and T2sc01_07_t1 ~~ sc01_07_t2 # This allows residual covariance on indicator X7 across T1 and T2sc01_08_t1 ~~ sc01_08_t2 # This allows residual covariance on indicator X8 across T1 and T2sc01_09_t1 ~~ sc01_09_t2 # This allows residual covariance on indicator X9 across T1 and T2sc01_10_t1 ~~ sc01_10_t2 # This allows residual covariance on indicator X10 across T1 and T2sc01_11_t1 ~~ sc01_11_t2 # This allows residual covariance on indicator X11 across T1 and T2sc01_12_t1 ~~ sc01_12_t2 # This allows residual covariance on indicator X12 across T1 and T2sc01_01_t1 ~~ res1*sc01_01_t1 # This allows residual variance on indicator X1 at T1 sc01_02_t1 ~~ res2*sc01_02_t1 # This allows residual variance on indicator X2 at T1sc01_03_t1 ~~ res3*sc01_03_t1 # This allows residual variance on indicator X3 at T1sc01_04_t1 ~~ res4*sc01_04_t1 # This allows residual variance on indicator X4 at T1sc01_05_t1 ~~ res5*sc01_05_t1 # This allows residual variance on indicator X5 at T1sc01_06_t1 ~~ res6*sc01_06_t1 # This allows residual variance on indicator X6 at T1 sc01_07_t1 ~~ res7*sc01_07_t1 # This allows residual variance on indicator X7 at T1sc01_08_t1 ~~ res8*sc01_08_t1 # This allows residual variance on indicator X8 at T1sc01_09_t1 ~~ res9*sc01_09_t1 # This allows residual variance on indicator X9 at T1sc01_10_t1 ~~ res10*sc01_10_t1 # This allows residual variance on indicator X10 at T1sc01_11_t1 ~~ res11*sc01_11_t1 # This allows residual variance on indicator X11 at T1sc01_12_t1 ~~ res12*sc01_12_t1 # This allows residual variance on indicator X12 at T1sc01_01_t2 ~~ res1*sc01_01_t2 # This allows residual variance on indicator X1 at T2 sc01_02_t2 ~~ res2*sc01_02_t2 # This allows residual variance on indicator X2 at T2 sc01_03_t2 ~~ res3*sc01_03_t2 # This allows residual variance on indicator X3 at T2sc01_04_t2 ~~ res4*sc01_04_t2 # This allows residual variance on indicator X4 at T2sc01_05_t2 ~~ res5*sc01_05_t2 # This allows residual variance on indicator X5 at T2sc01_06_t2 ~~ res6*sc01_06_t2 # This allows residual variance on indicator X6 at T2 sc01_07_t2 ~~ res7*sc01_07_t2 # This allows residual variance on indicator X7 at T2 sc01_08_t2 ~~ res8*sc01_08_t2 # This allows residual variance on indicator X8 at T2sc01_09_t2 ~~ res9*sc01_09_t2 # This allows residual variance on indicator X9 at T2sc01_10_t2 ~~ res10*sc01_10_t2 # This allows residual variance on indicator X10 at T2sc01_11_t2 ~~ res11*sc01_11_t2 # This allows residual variance on indicator X11 at T2sc01_12_t2 ~~ res12*sc01_12_t2 # This allows residual variance on indicator X12 at T2sc01_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1sc01_02_t1 ~ m2*1 # This estimates the intercept of X2 at T1sc01_03_t1 ~ m3*1 # This estimates the intercept of X3 at T1sc01_04_t1 ~ m4*1 # This estimates the intercept of X4 at T1sc01_05_t1 ~ m5*1 # This estimates the intercept of X5 at T1sc01_06_t1 ~ m6*1 # This estimates the intercept of X6 at T1sc01_07_t1 ~ m7*1 # This estimates the intercept of X7 at T1sc01_08_t1 ~ m8*1 # This estimates the intercept of X8 at T1sc01_09_t1 ~ m9*1 # This estimates the intercept of X9 at T1sc01_10_t1 ~ m10*1 # This estimates the intercept of X10 at T1sc01_11_t1 ~ m11*1 # This estimates the intercept of X11 at T1sc01_12_t1 ~ m12*1 # This estimates the intercept of X12 at T1sc01_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2sc01_02_t2 ~ m2*1 # This estimates the intercept of X2 at T2sc01_03_t2 ~ m3*1 # This estimates the intercept of X3 at T2sc01_04_t2 ~ m4*1 # This estimates the intercept of X4 at T2sc01_05_t2 ~ m5*1 # This estimates the intercept of X5 at T2sc01_06_t2 ~ m6*1 # This estimates the intercept of X6 at T2sc01_07_t2 ~ m7*1 # This estimates the intercept of X7 at T2sc01_08_t2 ~ m8*1 # This estimates the intercept of X8 at T2sc01_09_t2 ~ m9*1 # This estimates the intercept of X9 at T2sc01_10_t2 ~ m10*1 # This estimates the intercept of X10 at T2sc01_11_t2 ~ m11*1 # This estimates the intercept of X11 at T2sc01_12_t2 ~ m12*1 # This estimates the intercept of X12 at T2'fit_mi_lcs_concept_hyp2 <-lavaan(mi_lcs_concept_hyp2, data=df_sbsa_wide_wb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_concept_hyp2, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Self concept clarity improved significantly across time.
3.4 Hypothesis 3: Distance between ideal- and current-self over time
The distance between ideal- and current-self will decrease in both groups.
We will use two strategies to test this hypothesis. First, we will compute the Fisher z-transformed profile correlation between current- and ideal-self and test whether it increased across assessments. Second, we will test whether the squared difference between current- and ideal-self ratings for each Big Five trait decreased across assessments. We will test mean-level differences in profile correlations and squared differences between baseline and follow up using repeated-measures t-test.
3.4.1 Profile similarity
Reshape to wide:
Show the code
# reshape to widedf_sbsa_wide_profdiff <- df_sbsa %>%arrange(pid, time) %>%select(pid, time, profile_corr_item_z, profile_corr_facet_z, ends_with("_sqdiff")) %>%pivot_wider(names_from = time,names_sep ="_t",values_from =-c(pid, time))
profile_df_plot <- df_sbsa %>%select(pid, time, profile_corr_item_z, profile_corr_facet_z) %>%pivot_longer(-c(pid, time), names_to ="itemfacet", values_to ="corr") %>%mutate(itemfacet2 =fct_recode(itemfacet, "Item-level"="profile_corr_item_z", "Facet-level"="profile_corr_facet_z"),itemfacet2 =fct_reorder(itemfacet2, corr, .desc = F))ggplot(profile_df_plot) +aes(x =as.factor(time), y = corr) +geom_boxplot() +geom_violin(fill =NA) +facet_wrap(vars(itemfacet2)) +labs(x ="Measurement Occasion", y ="Profile correlation", title ="Hypothesis 3: Distance between ideal- and current-self") +theme_bw()
Significantly higher profile correlations at the second measurement occasion, both for the item-level profile correlation and the facet-level profile correlations.
Still very bad model fit. Strong measurement invariance according to chi^2 tests.
3.6 Hypothesis 4: Change goals and change in personality (current / ideal) in skill-building group
In the skill-building group, there will be a correlation between change goals and change in current-self ratings but not change in ideal-self ratings.
We will test this one domain/facet at a time. We will use both general continuous change goal score as well as trait-specific change goals. To test this hypothesis, we will estimate the mean-level differences across time for both current and ideal trait ratings using latent change models and correlate change goals with the change variable from those models.
3.6.1.1 Extraversion - current-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_curr_hyp4 <-'extra_t1 =~ 1*bf05_01_t1 + lamb2*bf05_06_t1 + lamb3*bf05_11_t1 + lamb4*bf05_16_t1 + lamb5*bf05_21_t1 + lamb6*bf05_26_t1 + lamb7*bf05_31_t1 + lamb8*bf05_36_t1 + lamb9*bf05_41_t1 + lamb10*bf05_46_t1 + lamb11*bf05_51_t1 + lamb12*bf05_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf05_01_t2 + lamb2*bf05_06_t2 + lamb3*bf05_11_t2 + lamb4*bf05_16_t2 + lamb5*bf05_21_t2 + lamb6*bf05_26_t2 + lamb7*bf05_31_t2 + lamb8*bf05_36_t2 + lamb9*bf05_41_t2 + lamb10*bf05_46_t2 + lamb11*bf05_51_t2 + lamb12*bf05_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsextra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf05_01_t1 ~~ bf05_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_06_t1 ~~ bf05_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_11_t1 ~~ bf05_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_16_t1 ~~ bf05_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_21_t1 ~~ bf05_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_26_t1 ~~ bf05_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_31_t1 ~~ bf05_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_36_t1 ~~ bf05_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_41_t1 ~~ bf05_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_46_t1 ~~ bf05_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_51_t1 ~~ bf05_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_56_t1 ~~ bf05_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_01_t1 ~~ res1*bf05_01_t1 # This allows residual variance on indicator X1 at T1 bf05_06_t1 ~~ res2*bf05_06_t1 # This allows residual variance on indicator X2 at T1bf05_11_t1 ~~ res3*bf05_11_t1 # This allows residual variance on indicator X3 at T1bf05_16_t1 ~~ res4*bf05_16_t1 # This allows residual variance on indicator X4 at T1bf05_21_t1 ~~ res5*bf05_21_t1 # This allows residual variance on indicator X5 at T1bf05_26_t1 ~~ res6*bf05_26_t1 # This allows residual variance on indicator X6 at T1 bf05_31_t1 ~~ res7*bf05_31_t1 # This allows residual variance on indicator X7 at T1bf05_36_t1 ~~ res8*bf05_36_t1 # This allows residual variance on indicator X8 at T1bf05_41_t1 ~~ res9*bf05_41_t1 # This allows residual variance on indicator X9 at T1bf05_46_t1 ~~ res10*bf05_46_t1 # This allows residual variance on indicator X10 at T1bf05_51_t1 ~~ res11*bf05_51_t1 # This allows residual variance on indicator X11 at T1bf05_56_t1 ~~ res12*bf05_56_t1 # This allows residual variance on indicator X12 at T1bf05_01_t2 ~~ res1*bf05_01_t2 # This allows residual variance on indicator X1 at T2 bf05_06_t2 ~~ res2*bf05_06_t2 # This allows residual variance on indicator X2 at T2 bf05_11_t2 ~~ res3*bf05_11_t2 # This allows residual variance on indicator X3 at T2bf05_16_t2 ~~ res4*bf05_16_t2 # This allows residual variance on indicator X4 at T2bf05_21_t2 ~~ res5*bf05_21_t2 # This allows residual variance on indicator X5 at T2bf05_26_t2 ~~ res6*bf05_26_t2 # This allows residual variance on indicator X6 at T2 bf05_31_t2 ~~ res7*bf05_31_t2 # This allows residual variance on indicator X7 at T2 bf05_36_t2 ~~ res8*bf05_36_t2 # This allows residual variance on indicator X8 at T2bf05_41_t2 ~~ res9*bf05_41_t2 # This allows residual variance on indicator X9 at T2bf05_46_t2 ~~ res10*bf05_46_t2 # This allows residual variance on indicator X10 at T2bf05_51_t2 ~~ res11*bf05_51_t2 # This allows residual variance on indicator X11 at T2bf05_56_t2 ~~ res12*bf05_56_t2 # This allows residual variance on indicator X12 at T2bf05_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_extra_curr_hyp4 <-lavaan(mi_lcs_extra_curr_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_curr_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
Correlation of general change goal with extraversion change score (current-self) is not significantly different from zero, r = 0.073, p = 0.065.
3.6.1.2 Extraversion - ideal-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_ideal_hyp4 <-'extra_t1 =~ 1*bf06_01_t1 + lamb2*bf06_06_t1 + lamb3*bf06_11_t1 + lamb4*bf06_16_t1 + lamb5*bf06_21_t1 + lamb6*bf06_26_t1 + lamb7*bf06_31_t1 + lamb8*bf06_36_t1 + lamb9*bf06_41_t1 + lamb10*bf06_46_t1 + lamb11*bf06_51_t1 + lamb12*bf06_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf06_01_t2 + lamb2*bf06_06_t2 + lamb3*bf06_11_t2 + lamb4*bf06_16_t2 + lamb5*bf06_21_t2 + lamb6*bf06_26_t2 + lamb7*bf06_31_t2 + lamb8*bf06_36_t2 + lamb9*bf06_41_t2 + lamb10*bf06_46_t2 + lamb11*bf06_51_t2 + lamb12*bf06_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsextra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf06_01_t1 ~~ bf06_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_06_t1 ~~ bf06_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_11_t1 ~~ bf06_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_16_t1 ~~ bf06_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_21_t1 ~~ bf06_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_26_t1 ~~ bf06_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_31_t1 ~~ bf06_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_36_t1 ~~ bf06_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_41_t1 ~~ bf06_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_46_t1 ~~ bf06_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_51_t1 ~~ bf06_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_56_t1 ~~ bf06_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_01_t1 ~~ res1*bf06_01_t1 # This allows residual variance on indicator X1 at T1 bf06_06_t1 ~~ res2*bf06_06_t1 # This allows residual variance on indicator X2 at T1bf06_11_t1 ~~ res3*bf06_11_t1 # This allows residual variance on indicator X3 at T1bf06_16_t1 ~~ res4*bf06_16_t1 # This allows residual variance on indicator X4 at T1bf06_21_t1 ~~ res5*bf06_21_t1 # This allows residual variance on indicator X5 at T1bf06_26_t1 ~~ res6*bf06_26_t1 # This allows residual variance on indicator X6 at T1 bf06_31_t1 ~~ res7*bf06_31_t1 # This allows residual variance on indicator X7 at T1bf06_36_t1 ~~ res8*bf06_36_t1 # This allows residual variance on indicator X8 at T1bf06_41_t1 ~~ res9*bf06_41_t1 # This allows residual variance on indicator X9 at T1bf06_46_t1 ~~ res10*bf06_46_t1 # This allows residual variance on indicator X10 at T1bf06_51_t1 ~~ res11*bf06_51_t1 # This allows residual variance on indicator X11 at T1bf06_56_t1 ~~ res12*bf06_56_t1 # This allows residual variance on indicator X12 at T1bf06_01_t2 ~~ res1*bf06_01_t2 # This allows residual variance on indicator X1 at T2 bf06_06_t2 ~~ res2*bf06_06_t2 # This allows residual variance on indicator X2 at T2 bf06_11_t2 ~~ res3*bf06_11_t2 # This allows residual variance on indicator X3 at T2bf06_16_t2 ~~ res4*bf06_16_t2 # This allows residual variance on indicator X4 at T2bf06_21_t2 ~~ res5*bf06_21_t2 # This allows residual variance on indicator X5 at T2bf06_26_t2 ~~ res6*bf06_26_t2 # This allows residual variance on indicator X6 at T2 bf06_31_t2 ~~ res7*bf06_31_t2 # This allows residual variance on indicator X7 at T2 bf06_36_t2 ~~ res8*bf06_36_t2 # This allows residual variance on indicator X8 at T2bf06_41_t2 ~~ res9*bf06_41_t2 # This allows residual variance on indicator X9 at T2bf06_46_t2 ~~ res10*bf06_46_t2 # This allows residual variance on indicator X10 at T2bf06_51_t2 ~~ res11*bf06_51_t2 # This allows residual variance on indicator X11 at T2bf06_56_t2 ~~ res12*bf06_56_t2 # This allows residual variance on indicator X12 at T2bf06_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_extra_ideal_hyp4 <-lavaan(mi_lcs_extra_ideal_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_ideal_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_curr_specif_hyp4 <-'extra_t1 =~ 1*bf05_01_t1 + lamb2*bf05_06_t1 + lamb3*bf05_11_t1 + lamb4*bf05_16_t1 + lamb5*bf05_21_t1 + lamb6*bf05_26_t1 + lamb7*bf05_31_t1 + lamb8*bf05_36_t1 + lamb9*bf05_41_t1 + lamb10*bf05_46_t1 + lamb11*bf05_51_t1 + lamb12*bf05_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf05_01_t2 + lamb2*bf05_06_t2 + lamb3*bf05_11_t2 + lamb4*bf05_16_t2 + lamb5*bf05_21_t2 + lamb6*bf05_26_t2 + lamb7*bf05_31_t2 + lamb8*bf05_36_t2 + lamb9*bf05_41_t2 + lamb10*bf05_46_t2 + lamb11*bf05_51_t2 + lamb12*bf05_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_01_t1 + sb07_02_t1 + sb07_03_t1 # latent change goal variable (three facets per trait)extra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf05_01_t1 ~~ bf05_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_06_t1 ~~ bf05_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_11_t1 ~~ bf05_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_16_t1 ~~ bf05_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_21_t1 ~~ bf05_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_26_t1 ~~ bf05_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_31_t1 ~~ bf05_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_36_t1 ~~ bf05_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_41_t1 ~~ bf05_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_46_t1 ~~ bf05_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_51_t1 ~~ bf05_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_56_t1 ~~ bf05_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_01_t1 ~~ res1*bf05_01_t1 # This allows residual variance on indicator X1 at T1 bf05_06_t1 ~~ res2*bf05_06_t1 # This allows residual variance on indicator X2 at T1bf05_11_t1 ~~ res3*bf05_11_t1 # This allows residual variance on indicator X3 at T1bf05_16_t1 ~~ res4*bf05_16_t1 # This allows residual variance on indicator X4 at T1bf05_21_t1 ~~ res5*bf05_21_t1 # This allows residual variance on indicator X5 at T1bf05_26_t1 ~~ res6*bf05_26_t1 # This allows residual variance on indicator X6 at T1 bf05_31_t1 ~~ res7*bf05_31_t1 # This allows residual variance on indicator X7 at T1bf05_36_t1 ~~ res8*bf05_36_t1 # This allows residual variance on indicator X8 at T1bf05_41_t1 ~~ res9*bf05_41_t1 # This allows residual variance on indicator X9 at T1bf05_46_t1 ~~ res10*bf05_46_t1 # This allows residual variance on indicator X10 at T1bf05_51_t1 ~~ res11*bf05_51_t1 # This allows residual variance on indicator X11 at T1bf05_56_t1 ~~ res12*bf05_56_t1 # This allows residual variance on indicator X12 at T1bf05_01_t2 ~~ res1*bf05_01_t2 # This allows residual variance on indicator X1 at T2 bf05_06_t2 ~~ res2*bf05_06_t2 # This allows residual variance on indicator X2 at T2 bf05_11_t2 ~~ res3*bf05_11_t2 # This allows residual variance on indicator X3 at T2bf05_16_t2 ~~ res4*bf05_16_t2 # This allows residual variance on indicator X4 at T2bf05_21_t2 ~~ res5*bf05_21_t2 # This allows residual variance on indicator X5 at T2bf05_26_t2 ~~ res6*bf05_26_t2 # This allows residual variance on indicator X6 at T2 bf05_31_t2 ~~ res7*bf05_31_t2 # This allows residual variance on indicator X7 at T2 bf05_36_t2 ~~ res8*bf05_36_t2 # This allows residual variance on indicator X8 at T2bf05_41_t2 ~~ res9*bf05_41_t2 # This allows residual variance on indicator X9 at T2bf05_46_t2 ~~ res10*bf05_46_t2 # This allows residual variance on indicator X10 at T2bf05_51_t2 ~~ res11*bf05_51_t2 # This allows residual variance on indicator X11 at T2bf05_56_t2 ~~ res12*bf05_56_t2 # This allows residual variance on indicator X12 at T2bf05_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_01_t1 ~~ sb07_01_t1sb07_02_t1 ~~ sb07_02_t1sb07_03_t1 ~~ sb07_03_t1sb07_01_t1 ~ 1sb07_02_t1 ~ 1sb07_03_t1 ~ 1'fit_mi_lcs_extra_curr_specif_hyp4 <-lavaan(mi_lcs_extra_curr_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_curr_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with extraversion change score (current-self) is not significantly different from zero, r = 0.012, p = 0.713.
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_ideal_specif_hyp4 <-'extra_t1 =~ 1*bf06_01_t1 + lamb2*bf06_06_t1 + lamb3*bf06_11_t1 + lamb4*bf06_16_t1 + lamb5*bf06_21_t1 + lamb6*bf06_26_t1 + lamb7*bf06_31_t1 + lamb8*bf06_36_t1 + lamb9*bf06_41_t1 + lamb10*bf06_46_t1 + lamb11*bf06_51_t1 + lamb12*bf06_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf06_01_t2 + lamb2*bf06_06_t2 + lamb3*bf06_11_t2 + lamb4*bf06_16_t2 + lamb5*bf06_21_t2 + lamb6*bf06_26_t2 + lamb7*bf06_31_t2 + lamb8*bf06_36_t2 + lamb9*bf06_41_t2 + lamb10*bf06_46_t2 + lamb11*bf06_51_t2 + lamb12*bf06_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_01_t1 + sb07_02_t1 + sb07_03_t1 # latent change goal variable (three facets per trait)extra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf06_01_t1 ~~ bf06_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_06_t1 ~~ bf06_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_11_t1 ~~ bf06_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_16_t1 ~~ bf06_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_21_t1 ~~ bf06_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_26_t1 ~~ bf06_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_31_t1 ~~ bf06_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_36_t1 ~~ bf06_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_41_t1 ~~ bf06_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_46_t1 ~~ bf06_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_51_t1 ~~ bf06_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_56_t1 ~~ bf06_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_01_t1 ~~ res1*bf06_01_t1 # This allows residual variance on indicator X1 at T1 bf06_06_t1 ~~ res2*bf06_06_t1 # This allows residual variance on indicator X2 at T1bf06_11_t1 ~~ res3*bf06_11_t1 # This allows residual variance on indicator X3 at T1bf06_16_t1 ~~ res4*bf06_16_t1 # This allows residual variance on indicator X4 at T1bf06_21_t1 ~~ res5*bf06_21_t1 # This allows residual variance on indicator X5 at T1bf06_26_t1 ~~ res6*bf06_26_t1 # This allows residual variance on indicator X6 at T1 bf06_31_t1 ~~ res7*bf06_31_t1 # This allows residual variance on indicator X7 at T1bf06_36_t1 ~~ res8*bf06_36_t1 # This allows residual variance on indicator X8 at T1bf06_41_t1 ~~ res9*bf06_41_t1 # This allows residual variance on indicator X9 at T1bf06_46_t1 ~~ res10*bf06_46_t1 # This allows residual variance on indicator X10 at T1bf06_51_t1 ~~ res11*bf06_51_t1 # This allows residual variance on indicator X11 at T1bf06_56_t1 ~~ res12*bf06_56_t1 # This allows residual variance on indicator X12 at T1bf06_01_t2 ~~ res1*bf06_01_t2 # This allows residual variance on indicator X1 at T2 bf06_06_t2 ~~ res2*bf06_06_t2 # This allows residual variance on indicator X2 at T2 bf06_11_t2 ~~ res3*bf06_11_t2 # This allows residual variance on indicator X3 at T2bf06_16_t2 ~~ res4*bf06_16_t2 # This allows residual variance on indicator X4 at T2bf06_21_t2 ~~ res5*bf06_21_t2 # This allows residual variance on indicator X5 at T2bf06_26_t2 ~~ res6*bf06_26_t2 # This allows residual variance on indicator X6 at T2 bf06_31_t2 ~~ res7*bf06_31_t2 # This allows residual variance on indicator X7 at T2 bf06_36_t2 ~~ res8*bf06_36_t2 # This allows residual variance on indicator X8 at T2bf06_41_t2 ~~ res9*bf06_41_t2 # This allows residual variance on indicator X9 at T2bf06_46_t2 ~~ res10*bf06_46_t2 # This allows residual variance on indicator X10 at T2bf06_51_t2 ~~ res11*bf06_51_t2 # This allows residual variance on indicator X11 at T2bf06_56_t2 ~~ res12*bf06_56_t2 # This allows residual variance on indicator X12 at T2bf06_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_01_t1 ~~ sb07_01_t1sb07_02_t1 ~~ sb07_02_t1sb07_03_t1 ~~ sb07_03_t1sb07_01_t1 ~ 1sb07_02_t1 ~ 1sb07_03_t1 ~ 1'fit_mi_lcs_extra_ideal_specif_hyp4 <-lavaan(mi_lcs_extra_ideal_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_ideal_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with extraversion change score (ideal-self) is not significantly different from zero, r = 0.012, p = 0.604.
3.6.1.5 Agreeableness - current-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_curr_hyp4 <-'agree_t1 =~ 1*bf05_02_t1 + lamb2*bf05_07_t1 + lamb3*bf05_12_t1 + lamb4*bf05_17_t1 + lamb5*bf05_22_t1 + lamb6*bf05_27_t1 + lamb7*bf05_32_t1 + lamb8*bf05_37_t1 + lamb9*bf05_42_t1 + lamb10*bf05_47_t1 + lamb11*bf05_52_t1 + lamb12*bf05_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf05_02_t2 + lamb2*bf05_07_t2 + lamb3*bf05_12_t2 + lamb4*bf05_17_t2 + lamb5*bf05_22_t2 + lamb6*bf05_27_t2 + lamb7*bf05_32_t2 + lamb8*bf05_37_t2 + lamb9*bf05_42_t2 + lamb10*bf05_47_t2 + lamb11*bf05_52_t2 + lamb12*bf05_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsagree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf05_02_t1 ~~ bf05_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_07_t1 ~~ bf05_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_12_t1 ~~ bf05_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_17_t1 ~~ bf05_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_22_t1 ~~ bf05_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_27_t1 ~~ bf05_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_32_t1 ~~ bf05_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_37_t1 ~~ bf05_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_42_t1 ~~ bf05_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_47_t1 ~~ bf05_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_52_t1 ~~ bf05_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_57_t1 ~~ bf05_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_02_t1 ~~ res1*bf05_02_t1 # This allows residual variance on indicator X1 at T1 bf05_07_t1 ~~ res2*bf05_07_t1 # This allows residual variance on indicator X2 at T1bf05_12_t1 ~~ res3*bf05_12_t1 # This allows residual variance on indicator X3 at T1bf05_17_t1 ~~ res4*bf05_17_t1 # This allows residual variance on indicator X4 at T1bf05_22_t1 ~~ res5*bf05_22_t1 # This allows residual variance on indicator X5 at T1bf05_27_t1 ~~ res6*bf05_27_t1 # This allows residual variance on indicator X6 at T1 bf05_32_t1 ~~ res7*bf05_32_t1 # This allows residual variance on indicator X7 at T1bf05_37_t1 ~~ res8*bf05_37_t1 # This allows residual variance on indicator X8 at T1bf05_42_t1 ~~ res9*bf05_42_t1 # This allows residual variance on indicator X9 at T1bf05_47_t1 ~~ res10*bf05_47_t1 # This allows residual variance on indicator X10 at T1bf05_52_t1 ~~ res11*bf05_52_t1 # This allows residual variance on indicator X11 at T1bf05_57_t1 ~~ res12*bf05_57_t1 # This allows residual variance on indicator X12 at T1bf05_02_t2 ~~ res1*bf05_02_t2 # This allows residual variance on indicator X1 at T2 bf05_07_t2 ~~ res2*bf05_07_t2 # This allows residual variance on indicator X2 at T2 bf05_12_t2 ~~ res3*bf05_12_t2 # This allows residual variance on indicator X3 at T2bf05_17_t2 ~~ res4*bf05_17_t2 # This allows residual variance on indicator X4 at T2bf05_22_t2 ~~ res5*bf05_22_t2 # This allows residual variance on indicator X5 at T2bf05_27_t2 ~~ res6*bf05_27_t2 # This allows residual variance on indicator X6 at T2 bf05_32_t2 ~~ res7*bf05_32_t2 # This allows residual variance on indicator X7 at T2 bf05_37_t2 ~~ res8*bf05_37_t2 # This allows residual variance on indicator X8 at T2bf05_42_t2 ~~ res9*bf05_42_t2 # This allows residual variance on indicator X9 at T2bf05_47_t2 ~~ res10*bf05_47_t2 # This allows residual variance on indicator X10 at T2bf05_52_t2 ~~ res11*bf05_52_t2 # This allows residual variance on indicator X11 at T2bf05_57_t2 ~~ res12*bf05_57_t2 # This allows residual variance on indicator X12 at T2bf05_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_agree_curr_hyp4 <-lavaan(mi_lcs_agree_curr_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_curr_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
Correlation of general change goal with agreeableness change score (current-self) is not significantly different from zero, r = -0.007, p = 0.742.
3.6.1.6 Agreeableness - ideal-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_ideal_hyp4 <-'agree_t1 =~ 1*bf06_02_t1 + lamb2*bf06_07_t1 + lamb3*bf06_12_t1 + lamb4*bf06_17_t1 + lamb5*bf06_22_t1 + lamb6*bf06_27_t1 + lamb7*bf06_32_t1 + lamb8*bf06_37_t1 + lamb9*bf06_42_t1 + lamb10*bf06_47_t1 + lamb11*bf06_52_t1 + lamb12*bf06_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf06_02_t2 + lamb2*bf06_07_t2 + lamb3*bf06_12_t2 + lamb4*bf06_17_t2 + lamb5*bf06_22_t2 + lamb6*bf06_27_t2 + lamb7*bf06_32_t2 + lamb8*bf06_37_t2 + lamb9*bf06_42_t2 + lamb10*bf06_47_t2 + lamb11*bf06_52_t2 + lamb12*bf06_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsagree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf06_02_t1 ~~ bf06_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_07_t1 ~~ bf06_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_12_t1 ~~ bf06_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_17_t1 ~~ bf06_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_22_t1 ~~ bf06_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_27_t1 ~~ bf06_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_32_t1 ~~ bf06_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_37_t1 ~~ bf06_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_42_t1 ~~ bf06_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_47_t1 ~~ bf06_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_52_t1 ~~ bf06_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_57_t1 ~~ bf06_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_02_t1 ~~ res1*bf06_02_t1 # This allows residual variance on indicator X1 at T1 bf06_07_t1 ~~ res2*bf06_07_t1 # This allows residual variance on indicator X2 at T1bf06_12_t1 ~~ res3*bf06_12_t1 # This allows residual variance on indicator X3 at T1bf06_17_t1 ~~ res4*bf06_17_t1 # This allows residual variance on indicator X4 at T1bf06_22_t1 ~~ res5*bf06_22_t1 # This allows residual variance on indicator X5 at T1bf06_27_t1 ~~ res6*bf06_27_t1 # This allows residual variance on indicator X6 at T1 bf06_32_t1 ~~ res7*bf06_32_t1 # This allows residual variance on indicator X7 at T1bf06_37_t1 ~~ res8*bf06_37_t1 # This allows residual variance on indicator X8 at T1bf06_42_t1 ~~ res9*bf06_42_t1 # This allows residual variance on indicator X9 at T1bf06_47_t1 ~~ res10*bf06_47_t1 # This allows residual variance on indicator X10 at T1bf06_52_t1 ~~ res11*bf06_52_t1 # This allows residual variance on indicator X11 at T1bf06_57_t1 ~~ res12*bf06_57_t1 # This allows residual variance on indicator X12 at T1bf06_02_t2 ~~ res1*bf06_02_t2 # This allows residual variance on indicator X1 at T2 bf06_07_t2 ~~ res2*bf06_07_t2 # This allows residual variance on indicator X2 at T2 bf06_12_t2 ~~ res3*bf06_12_t2 # This allows residual variance on indicator X3 at T2bf06_17_t2 ~~ res4*bf06_17_t2 # This allows residual variance on indicator X4 at T2bf06_22_t2 ~~ res5*bf06_22_t2 # This allows residual variance on indicator X5 at T2bf06_27_t2 ~~ res6*bf06_27_t2 # This allows residual variance on indicator X6 at T2 bf06_32_t2 ~~ res7*bf06_32_t2 # This allows residual variance on indicator X7 at T2 bf06_37_t2 ~~ res8*bf06_37_t2 # This allows residual variance on indicator X8 at T2bf06_42_t2 ~~ res9*bf06_42_t2 # This allows residual variance on indicator X9 at T2bf06_47_t2 ~~ res10*bf06_47_t2 # This allows residual variance on indicator X10 at T2bf06_52_t2 ~~ res11*bf06_52_t2 # This allows residual variance on indicator X11 at T2bf06_57_t2 ~~ res12*bf06_57_t2 # This allows residual variance on indicator X12 at T2bf06_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_agree_ideal_hyp4 <-lavaan(mi_lcs_agree_ideal_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_ideal_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_curr_specif_hyp4 <-'agree_t1 =~ 1*bf05_02_t1 + lamb2*bf05_07_t1 + lamb3*bf05_12_t1 + lamb4*bf05_17_t1 + lamb5*bf05_22_t1 + lamb6*bf05_27_t1 + lamb7*bf05_32_t1 + lamb8*bf05_37_t1 + lamb9*bf05_42_t1 + lamb10*bf05_47_t1 + lamb11*bf05_52_t1 + lamb12*bf05_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf05_02_t2 + lamb2*bf05_07_t2 + lamb3*bf05_12_t2 + lamb4*bf05_17_t2 + lamb5*bf05_22_t2 + lamb6*bf05_27_t2 + lamb7*bf05_32_t2 + lamb8*bf05_37_t2 + lamb9*bf05_42_t2 + lamb10*bf05_47_t2 + lamb11*bf05_52_t2 + lamb12*bf05_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_04_t1 + sb07_05_t1 + sb07_06_t1 # latent change goal variable (three facets per trait)agree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf05_02_t1 ~~ bf05_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_07_t1 ~~ bf05_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_12_t1 ~~ bf05_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_17_t1 ~~ bf05_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_22_t1 ~~ bf05_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_27_t1 ~~ bf05_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_32_t1 ~~ bf05_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_37_t1 ~~ bf05_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_42_t1 ~~ bf05_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_47_t1 ~~ bf05_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_52_t1 ~~ bf05_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_57_t1 ~~ bf05_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_02_t1 ~~ res1*bf05_02_t1 # This allows residual variance on indicator X1 at T1 bf05_07_t1 ~~ res2*bf05_07_t1 # This allows residual variance on indicator X2 at T1bf05_12_t1 ~~ res3*bf05_12_t1 # This allows residual variance on indicator X3 at T1bf05_17_t1 ~~ res4*bf05_17_t1 # This allows residual variance on indicator X4 at T1bf05_22_t1 ~~ res5*bf05_22_t1 # This allows residual variance on indicator X5 at T1bf05_27_t1 ~~ res6*bf05_27_t1 # This allows residual variance on indicator X6 at T1 bf05_32_t1 ~~ res7*bf05_32_t1 # This allows residual variance on indicator X7 at T1bf05_37_t1 ~~ res8*bf05_37_t1 # This allows residual variance on indicator X8 at T1bf05_42_t1 ~~ res9*bf05_42_t1 # This allows residual variance on indicator X9 at T1bf05_47_t1 ~~ res10*bf05_47_t1 # This allows residual variance on indicator X10 at T1bf05_52_t1 ~~ res11*bf05_52_t1 # This allows residual variance on indicator X11 at T1bf05_57_t1 ~~ res12*bf05_57_t1 # This allows residual variance on indicator X12 at T1bf05_02_t2 ~~ res1*bf05_02_t2 # This allows residual variance on indicator X1 at T2 bf05_07_t2 ~~ res2*bf05_07_t2 # This allows residual variance on indicator X2 at T2 bf05_12_t2 ~~ res3*bf05_12_t2 # This allows residual variance on indicator X3 at T2bf05_17_t2 ~~ res4*bf05_17_t2 # This allows residual variance on indicator X4 at T2bf05_22_t2 ~~ res5*bf05_22_t2 # This allows residual variance on indicator X5 at T2bf05_27_t2 ~~ res6*bf05_27_t2 # This allows residual variance on indicator X6 at T2 bf05_32_t2 ~~ res7*bf05_32_t2 # This allows residual variance on indicator X7 at T2 bf05_37_t2 ~~ res8*bf05_37_t2 # This allows residual variance on indicator X8 at T2bf05_42_t2 ~~ res9*bf05_42_t2 # This allows residual variance on indicator X9 at T2bf05_47_t2 ~~ res10*bf05_47_t2 # This allows residual variance on indicator X10 at T2bf05_52_t2 ~~ res11*bf05_52_t2 # This allows residual variance on indicator X11 at T2bf05_57_t2 ~~ res12*bf05_57_t2 # This allows residual variance on indicator X12 at T2bf05_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_04_t1 ~~ sb07_04_t1sb07_05_t1 ~~ sb07_05_t1sb07_06_t1 ~~ sb07_06_t1sb07_04_t1 ~ 1sb07_05_t1 ~ 1sb07_06_t1 ~ 1'fit_mi_lcs_agree_curr_specif_hyp4 <-lavaan(mi_lcs_agree_curr_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_curr_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with agreeableness change score (current-self) is not significantly different from zero, r = 0.018, p = 0.481.
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_ideal_specif_hyp4 <-'agree_t1 =~ 1*bf06_02_t1 + lamb2*bf06_07_t1 + lamb3*bf06_12_t1 + lamb4*bf06_17_t1 + lamb5*bf06_22_t1 + lamb6*bf06_27_t1 + lamb7*bf06_32_t1 + lamb8*bf06_37_t1 + lamb9*bf06_42_t1 + lamb10*bf06_47_t1 + lamb11*bf06_52_t1 + lamb12*bf06_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf06_02_t2 + lamb2*bf06_07_t2 + lamb3*bf06_12_t2 + lamb4*bf06_17_t2 + lamb5*bf06_22_t2 + lamb6*bf06_27_t2 + lamb7*bf06_32_t2 + lamb8*bf06_37_t2 + lamb9*bf06_42_t2 + lamb10*bf06_47_t2 + lamb11*bf06_52_t2 + lamb12*bf06_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_04_t1 + sb07_05_t1 + sb07_06_t1 # latent change goal variable (three facets per trait)agree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf06_02_t1 ~~ bf06_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_07_t1 ~~ bf06_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_12_t1 ~~ bf06_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_17_t1 ~~ bf06_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_22_t1 ~~ bf06_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_27_t1 ~~ bf06_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_32_t1 ~~ bf06_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_37_t1 ~~ bf06_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_42_t1 ~~ bf06_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_47_t1 ~~ bf06_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_52_t1 ~~ bf06_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_57_t1 ~~ bf06_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_02_t1 ~~ res1*bf06_02_t1 # This allows residual variance on indicator X1 at T1 bf06_07_t1 ~~ res2*bf06_07_t1 # This allows residual variance on indicator X2 at T1bf06_12_t1 ~~ res3*bf06_12_t1 # This allows residual variance on indicator X3 at T1bf06_17_t1 ~~ res4*bf06_17_t1 # This allows residual variance on indicator X4 at T1bf06_22_t1 ~~ res5*bf06_22_t1 # This allows residual variance on indicator X5 at T1bf06_27_t1 ~~ res6*bf06_27_t1 # This allows residual variance on indicator X6 at T1 bf06_32_t1 ~~ res7*bf06_32_t1 # This allows residual variance on indicator X7 at T1bf06_37_t1 ~~ res8*bf06_37_t1 # This allows residual variance on indicator X8 at T1bf06_42_t1 ~~ res9*bf06_42_t1 # This allows residual variance on indicator X9 at T1bf06_47_t1 ~~ res10*bf06_47_t1 # This allows residual variance on indicator X10 at T1bf06_52_t1 ~~ res11*bf06_52_t1 # This allows residual variance on indicator X11 at T1bf06_57_t1 ~~ res12*bf06_57_t1 # This allows residual variance on indicator X12 at T1bf06_02_t2 ~~ res1*bf06_02_t2 # This allows residual variance on indicator X1 at T2 bf06_07_t2 ~~ res2*bf06_07_t2 # This allows residual variance on indicator X2 at T2 bf06_12_t2 ~~ res3*bf06_12_t2 # This allows residual variance on indicator X3 at T2bf06_17_t2 ~~ res4*bf06_17_t2 # This allows residual variance on indicator X4 at T2bf06_22_t2 ~~ res5*bf06_22_t2 # This allows residual variance on indicator X5 at T2bf06_27_t2 ~~ res6*bf06_27_t2 # This allows residual variance on indicator X6 at T2 bf06_32_t2 ~~ res7*bf06_32_t2 # This allows residual variance on indicator X7 at T2 bf06_37_t2 ~~ res8*bf06_37_t2 # This allows residual variance on indicator X8 at T2bf06_42_t2 ~~ res9*bf06_42_t2 # This allows residual variance on indicator X9 at T2bf06_47_t2 ~~ res10*bf06_47_t2 # This allows residual variance on indicator X10 at T2bf06_52_t2 ~~ res11*bf06_52_t2 # This allows residual variance on indicator X11 at T2bf06_57_t2 ~~ res12*bf06_57_t2 # This allows residual variance on indicator X12 at T2bf06_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_04_t1 ~~ sb07_04_t1sb07_05_t1 ~~ sb07_05_t1sb07_06_t1 ~~ sb07_06_t1sb07_04_t1 ~ 1sb07_05_t1 ~ 1sb07_06_t1 ~ 1'fit_mi_lcs_agree_ideal_specif_hyp4 <-lavaan(mi_lcs_agree_ideal_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_ideal_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with agreeableness change score (ideal-self) is not significantly different from zero, r = -0.04, p = 0.171.
3.6.1.9 Conscientiousness - current-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_curr_hyp4 <-'consc_t1 =~ 1*bf05_03_t1 + lamb2*bf05_08_t1 + lamb3*bf05_13_t1 + lamb4*bf05_18_t1 + lamb5*bf05_23_t1 + lamb6*bf05_28_t1 + lamb7*bf05_33_t1 + lamb8*bf05_38_t1 + lamb9*bf05_43_t1 + lamb10*bf05_48_t1 + lamb11*bf05_53_t1 + lamb12*bf05_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf05_03_t2 + lamb2*bf05_08_t2 + lamb3*bf05_13_t2 + lamb4*bf05_18_t2 + lamb5*bf05_23_t2 + lamb6*bf05_28_t2 + lamb7*bf05_33_t2 + lamb8*bf05_38_t2 + lamb9*bf05_43_t2 + lamb10*bf05_48_t2 + lamb11*bf05_53_t2 + lamb12*bf05_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsconsc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf05_03_t1 ~~ bf05_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_08_t1 ~~ bf05_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_13_t1 ~~ bf05_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_18_t1 ~~ bf05_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_23_t1 ~~ bf05_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_28_t1 ~~ bf05_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_33_t1 ~~ bf05_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_38_t1 ~~ bf05_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_43_t1 ~~ bf05_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_48_t1 ~~ bf05_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_53_t1 ~~ bf05_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_58_t1 ~~ bf05_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_03_t1 ~~ res1*bf05_03_t1 # This allows residual variance on indicator X1 at T1 bf05_08_t1 ~~ res2*bf05_08_t1 # This allows residual variance on indicator X2 at T1bf05_13_t1 ~~ res3*bf05_13_t1 # This allows residual variance on indicator X3 at T1bf05_18_t1 ~~ res4*bf05_18_t1 # This allows residual variance on indicator X4 at T1bf05_23_t1 ~~ res5*bf05_23_t1 # This allows residual variance on indicator X5 at T1bf05_28_t1 ~~ res6*bf05_28_t1 # This allows residual variance on indicator X6 at T1 bf05_33_t1 ~~ res7*bf05_33_t1 # This allows residual variance on indicator X7 at T1bf05_38_t1 ~~ res8*bf05_38_t1 # This allows residual variance on indicator X8 at T1bf05_43_t1 ~~ res9*bf05_43_t1 # This allows residual variance on indicator X9 at T1bf05_48_t1 ~~ res10*bf05_48_t1 # This allows residual variance on indicator X10 at T1bf05_53_t1 ~~ res11*bf05_53_t1 # This allows residual variance on indicator X11 at T1bf05_58_t1 ~~ res12*bf05_58_t1 # This allows residual variance on indicator X12 at T1bf05_03_t2 ~~ res1*bf05_03_t2 # This allows residual variance on indicator X1 at T2 bf05_08_t2 ~~ res2*bf05_08_t2 # This allows residual variance on indicator X2 at T2 bf05_13_t2 ~~ res3*bf05_13_t2 # This allows residual variance on indicator X3 at T2bf05_18_t2 ~~ res4*bf05_18_t2 # This allows residual variance on indicator X4 at T2bf05_23_t2 ~~ res5*bf05_23_t2 # This allows residual variance on indicator X5 at T2bf05_28_t2 ~~ res6*bf05_28_t2 # This allows residual variance on indicator X6 at T2 bf05_33_t2 ~~ res7*bf05_33_t2 # This allows residual variance on indicator X7 at T2 bf05_38_t2 ~~ res8*bf05_38_t2 # This allows residual variance on indicator X8 at T2bf05_43_t2 ~~ res9*bf05_43_t2 # This allows residual variance on indicator X9 at T2bf05_48_t2 ~~ res10*bf05_48_t2 # This allows residual variance on indicator X10 at T2bf05_53_t2 ~~ res11*bf05_53_t2 # This allows residual variance on indicator X11 at T2bf05_58_t2 ~~ res12*bf05_58_t2 # This allows residual variance on indicator X12 at T2bf05_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_consc_curr_hyp4 <-lavaan(mi_lcs_consc_curr_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_curr_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
Correlation of general change goal with conscientiousness change score (current-self) is not significantly different from zero, r = -0.022, p = 0.506.
3.6.1.10 Conscientiousness - ideal-self: general change goals
Fit model:
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# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_ideal_hyp4 <-'consc_t1 =~ 1*bf06_03_t1 + lamb2*bf06_08_t1 + lamb3*bf06_13_t1 + lamb4*bf06_18_t1 + lamb5*bf06_23_t1 + lamb6*bf06_28_t1 + lamb7*bf06_33_t1 + lamb8*bf06_38_t1 + lamb9*bf06_43_t1 + lamb10*bf06_48_t1 + lamb11*bf06_53_t1 + lamb12*bf06_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf06_03_t2 + lamb2*bf06_08_t2 + lamb3*bf06_13_t2 + lamb4*bf06_18_t2 + lamb5*bf06_23_t2 + lamb6*bf06_28_t2 + lamb7*bf06_33_t2 + lamb8*bf06_38_t2 + lamb9*bf06_43_t2 + lamb10*bf06_48_t2 + lamb11*bf06_53_t2 + lamb12*bf06_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsconsc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf06_03_t1 ~~ bf06_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_08_t1 ~~ bf06_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_13_t1 ~~ bf06_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_18_t1 ~~ bf06_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_23_t1 ~~ bf06_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_28_t1 ~~ bf06_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_33_t1 ~~ bf06_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_38_t1 ~~ bf06_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_43_t1 ~~ bf06_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_48_t1 ~~ bf06_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_53_t1 ~~ bf06_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_58_t1 ~~ bf06_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_03_t1 ~~ res1*bf06_03_t1 # This allows residual variance on indicator X1 at T1 bf06_08_t1 ~~ res2*bf06_08_t1 # This allows residual variance on indicator X2 at T1bf06_13_t1 ~~ res3*bf06_13_t1 # This allows residual variance on indicator X3 at T1bf06_18_t1 ~~ res4*bf06_18_t1 # This allows residual variance on indicator X4 at T1bf06_23_t1 ~~ res5*bf06_23_t1 # This allows residual variance on indicator X5 at T1bf06_28_t1 ~~ res6*bf06_28_t1 # This allows residual variance on indicator X6 at T1 bf06_33_t1 ~~ res7*bf06_33_t1 # This allows residual variance on indicator X7 at T1bf06_38_t1 ~~ res8*bf06_38_t1 # This allows residual variance on indicator X8 at T1bf06_43_t1 ~~ res9*bf06_43_t1 # This allows residual variance on indicator X9 at T1bf06_48_t1 ~~ res10*bf06_48_t1 # This allows residual variance on indicator X10 at T1bf06_53_t1 ~~ res11*bf06_53_t1 # This allows residual variance on indicator X11 at T1bf06_58_t1 ~~ res12*bf06_58_t1 # This allows residual variance on indicator X12 at T1bf06_03_t2 ~~ res1*bf06_03_t2 # This allows residual variance on indicator X1 at T2 bf06_08_t2 ~~ res2*bf06_08_t2 # This allows residual variance on indicator X2 at T2 bf06_13_t2 ~~ res3*bf06_13_t2 # This allows residual variance on indicator X3 at T2bf06_18_t2 ~~ res4*bf06_18_t2 # This allows residual variance on indicator X4 at T2bf06_23_t2 ~~ res5*bf06_23_t2 # This allows residual variance on indicator X5 at T2bf06_28_t2 ~~ res6*bf06_28_t2 # This allows residual variance on indicator X6 at T2 bf06_33_t2 ~~ res7*bf06_33_t2 # This allows residual variance on indicator X7 at T2 bf06_38_t2 ~~ res8*bf06_38_t2 # This allows residual variance on indicator X8 at T2bf06_43_t2 ~~ res9*bf06_43_t2 # This allows residual variance on indicator X9 at T2bf06_48_t2 ~~ res10*bf06_48_t2 # This allows residual variance on indicator X10 at T2bf06_53_t2 ~~ res11*bf06_53_t2 # This allows residual variance on indicator X11 at T2bf06_58_t2 ~~ res12*bf06_58_t2 # This allows residual variance on indicator X12 at T2bf06_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_consc_ideal_hyp4 <-lavaan(mi_lcs_consc_ideal_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_ideal_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_curr_specif_hyp4 <-'consc_t1 =~ 1*bf05_03_t1 + lamb2*bf05_08_t1 + lamb3*bf05_13_t1 + lamb4*bf05_18_t1 + lamb5*bf05_23_t1 + lamb6*bf05_28_t1 + lamb7*bf05_33_t1 + lamb8*bf05_38_t1 + lamb9*bf05_43_t1 + lamb10*bf05_48_t1 + lamb11*bf05_53_t1 + lamb12*bf05_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf05_03_t2 + lamb2*bf05_08_t2 + lamb3*bf05_13_t2 + lamb4*bf05_18_t2 + lamb5*bf05_23_t2 + lamb6*bf05_28_t2 + lamb7*bf05_33_t2 + lamb8*bf05_38_t2 + lamb9*bf05_43_t2 + lamb10*bf05_48_t2 + lamb11*bf05_53_t2 + lamb12*bf05_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_07_t1 + sb07_08_t1 + sb07_09_t1 # latent change goal variable (three facets per trait)consc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf05_03_t1 ~~ bf05_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_08_t1 ~~ bf05_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_13_t1 ~~ bf05_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_18_t1 ~~ bf05_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_23_t1 ~~ bf05_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_28_t1 ~~ bf05_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_33_t1 ~~ bf05_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_38_t1 ~~ bf05_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_43_t1 ~~ bf05_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_48_t1 ~~ bf05_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_53_t1 ~~ bf05_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_58_t1 ~~ bf05_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_03_t1 ~~ res1*bf05_03_t1 # This allows residual variance on indicator X1 at T1 bf05_08_t1 ~~ res2*bf05_08_t1 # This allows residual variance on indicator X2 at T1bf05_13_t1 ~~ res3*bf05_13_t1 # This allows residual variance on indicator X3 at T1bf05_18_t1 ~~ res4*bf05_18_t1 # This allows residual variance on indicator X4 at T1bf05_23_t1 ~~ res5*bf05_23_t1 # This allows residual variance on indicator X5 at T1bf05_28_t1 ~~ res6*bf05_28_t1 # This allows residual variance on indicator X6 at T1 bf05_33_t1 ~~ res7*bf05_33_t1 # This allows residual variance on indicator X7 at T1bf05_38_t1 ~~ res8*bf05_38_t1 # This allows residual variance on indicator X8 at T1bf05_43_t1 ~~ res9*bf05_43_t1 # This allows residual variance on indicator X9 at T1bf05_48_t1 ~~ res10*bf05_48_t1 # This allows residual variance on indicator X10 at T1bf05_53_t1 ~~ res11*bf05_53_t1 # This allows residual variance on indicator X11 at T1bf05_58_t1 ~~ res12*bf05_58_t1 # This allows residual variance on indicator X12 at T1bf05_03_t2 ~~ res1*bf05_03_t2 # This allows residual variance on indicator X1 at T2 bf05_08_t2 ~~ res2*bf05_08_t2 # This allows residual variance on indicator X2 at T2 bf05_13_t2 ~~ res3*bf05_13_t2 # This allows residual variance on indicator X3 at T2bf05_18_t2 ~~ res4*bf05_18_t2 # This allows residual variance on indicator X4 at T2bf05_23_t2 ~~ res5*bf05_23_t2 # This allows residual variance on indicator X5 at T2bf05_28_t2 ~~ res6*bf05_28_t2 # This allows residual variance on indicator X6 at T2 bf05_33_t2 ~~ res7*bf05_33_t2 # This allows residual variance on indicator X7 at T2 bf05_38_t2 ~~ res8*bf05_38_t2 # This allows residual variance on indicator X8 at T2bf05_43_t2 ~~ res9*bf05_43_t2 # This allows residual variance on indicator X9 at T2bf05_48_t2 ~~ res10*bf05_48_t2 # This allows residual variance on indicator X10 at T2bf05_53_t2 ~~ res11*bf05_53_t2 # This allows residual variance on indicator X11 at T2bf05_58_t2 ~~ res12*bf05_58_t2 # This allows residual variance on indicator X12 at T2bf05_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_07_t1 ~~ sb07_07_t1sb07_08_t1 ~~ sb07_08_t1sb07_09_t1 ~~ sb07_09_t1sb07_07_t1 ~ 1sb07_08_t1 ~ 1sb07_09_t1 ~ 1'fit_mi_lcs_consc_curr_specif_hyp4 <-lavaan(mi_lcs_consc_curr_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_curr_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with conscientiousness change score (current-self) is not significantly different from zero, r = 0.011, p = 0.822.
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_ideal_specif_hyp4 <-'consc_t1 =~ 1*bf06_03_t1 + lamb2*bf06_08_t1 + lamb3*bf06_13_t1 + lamb4*bf06_18_t1 + lamb5*bf06_23_t1 + lamb6*bf06_28_t1 + lamb7*bf06_33_t1 + lamb8*bf06_38_t1 + lamb9*bf06_43_t1 + lamb10*bf06_48_t1 + lamb11*bf06_53_t1 + lamb12*bf06_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf06_03_t2 + lamb2*bf06_08_t2 + lamb3*bf06_13_t2 + lamb4*bf06_18_t2 + lamb5*bf06_23_t2 + lamb6*bf06_28_t2 + lamb7*bf06_33_t2 + lamb8*bf06_38_t2 + lamb9*bf06_43_t2 + lamb10*bf06_48_t2 + lamb11*bf06_53_t2 + lamb12*bf06_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_07_t1 + sb07_08_t1 + sb07_09_t1 # latent change goal variable (three facets per trait)consc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf06_03_t1 ~~ bf06_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_08_t1 ~~ bf06_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_13_t1 ~~ bf06_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_18_t1 ~~ bf06_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_23_t1 ~~ bf06_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_28_t1 ~~ bf06_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_33_t1 ~~ bf06_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_38_t1 ~~ bf06_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_43_t1 ~~ bf06_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_48_t1 ~~ bf06_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_53_t1 ~~ bf06_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_58_t1 ~~ bf06_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_03_t1 ~~ res1*bf06_03_t1 # This allows residual variance on indicator X1 at T1 bf06_08_t1 ~~ res2*bf06_08_t1 # This allows residual variance on indicator X2 at T1bf06_13_t1 ~~ res3*bf06_13_t1 # This allows residual variance on indicator X3 at T1bf06_18_t1 ~~ res4*bf06_18_t1 # This allows residual variance on indicator X4 at T1bf06_23_t1 ~~ res5*bf06_23_t1 # This allows residual variance on indicator X5 at T1bf06_28_t1 ~~ res6*bf06_28_t1 # This allows residual variance on indicator X6 at T1 bf06_33_t1 ~~ res7*bf06_33_t1 # This allows residual variance on indicator X7 at T1bf06_38_t1 ~~ res8*bf06_38_t1 # This allows residual variance on indicator X8 at T1bf06_43_t1 ~~ res9*bf06_43_t1 # This allows residual variance on indicator X9 at T1bf06_48_t1 ~~ res10*bf06_48_t1 # This allows residual variance on indicator X10 at T1bf06_53_t1 ~~ res11*bf06_53_t1 # This allows residual variance on indicator X11 at T1bf06_58_t1 ~~ res12*bf06_58_t1 # This allows residual variance on indicator X12 at T1bf06_03_t2 ~~ res1*bf06_03_t2 # This allows residual variance on indicator X1 at T2 bf06_08_t2 ~~ res2*bf06_08_t2 # This allows residual variance on indicator X2 at T2 bf06_13_t2 ~~ res3*bf06_13_t2 # This allows residual variance on indicator X3 at T2bf06_18_t2 ~~ res4*bf06_18_t2 # This allows residual variance on indicator X4 at T2bf06_23_t2 ~~ res5*bf06_23_t2 # This allows residual variance on indicator X5 at T2bf06_28_t2 ~~ res6*bf06_28_t2 # This allows residual variance on indicator X6 at T2 bf06_33_t2 ~~ res7*bf06_33_t2 # This allows residual variance on indicator X7 at T2 bf06_38_t2 ~~ res8*bf06_38_t2 # This allows residual variance on indicator X8 at T2bf06_43_t2 ~~ res9*bf06_43_t2 # This allows residual variance on indicator X9 at T2bf06_48_t2 ~~ res10*bf06_48_t2 # This allows residual variance on indicator X10 at T2bf06_53_t2 ~~ res11*bf06_53_t2 # This allows residual variance on indicator X11 at T2bf06_58_t2 ~~ res12*bf06_58_t2 # This allows residual variance on indicator X12 at T2bf06_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_07_t1 ~~ sb07_07_t1sb07_08_t1 ~~ sb07_08_t1sb07_09_t1 ~~ sb07_09_t1sb07_07_t1 ~ 1sb07_08_t1 ~ 1sb07_09_t1 ~ 1'fit_mi_lcs_consc_ideal_specif_hyp4 <-lavaan(mi_lcs_consc_ideal_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_ideal_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with conscientiousness change score (ideal-self) is not significantly different from zero, r = 0.027, p = 0.272.
3.6.1.13 Neuroticism - current-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_curr_hyp4 <-'neuro_t1 =~ 1*bf05_04_t1 + lamb2*bf05_09_t1 + lamb3*bf05_14_t1 + lamb4*bf05_19_t1 + lamb5*bf05_24_t1 + lamb6*bf05_29_t1 + lamb7*bf05_34_t1 + lamb8*bf05_39_t1 + lamb9*bf05_44_t1 + lamb10*bf05_49_t1 + lamb11*bf05_54_t1 + lamb12*bf05_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf05_04_t2 + lamb2*bf05_09_t2 + lamb3*bf05_14_t2 + lamb4*bf05_19_t2 + lamb5*bf05_24_t2 + lamb6*bf05_29_t2 + lamb7*bf05_34_t2 + lamb8*bf05_39_t2 + lamb9*bf05_44_t2 + lamb10*bf05_49_t2 + lamb11*bf05_54_t2 + lamb12*bf05_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsneuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf05_04_t1 ~~ bf05_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_09_t1 ~~ bf05_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_14_t1 ~~ bf05_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_19_t1 ~~ bf05_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_24_t1 ~~ bf05_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_29_t1 ~~ bf05_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_34_t1 ~~ bf05_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_39_t1 ~~ bf05_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_44_t1 ~~ bf05_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_49_t1 ~~ bf05_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_54_t1 ~~ bf05_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_59_t1 ~~ bf05_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_04_t1 ~~ res1*bf05_04_t1 # This allows residual variance on indicator X1 at T1 bf05_09_t1 ~~ res2*bf05_09_t1 # This allows residual variance on indicator X2 at T1bf05_14_t1 ~~ res3*bf05_14_t1 # This allows residual variance on indicator X3 at T1bf05_19_t1 ~~ res4*bf05_19_t1 # This allows residual variance on indicator X4 at T1bf05_24_t1 ~~ res5*bf05_24_t1 # This allows residual variance on indicator X5 at T1bf05_29_t1 ~~ res6*bf05_29_t1 # This allows residual variance on indicator X6 at T1 bf05_34_t1 ~~ res7*bf05_34_t1 # This allows residual variance on indicator X7 at T1bf05_39_t1 ~~ res8*bf05_39_t1 # This allows residual variance on indicator X8 at T1bf05_44_t1 ~~ res9*bf05_44_t1 # This allows residual variance on indicator X9 at T1bf05_49_t1 ~~ res10*bf05_49_t1 # This allows residual variance on indicator X10 at T1bf05_54_t1 ~~ res11*bf05_54_t1 # This allows residual variance on indicator X11 at T1bf05_59_t1 ~~ res12*bf05_59_t1 # This allows residual variance on indicator X12 at T1bf05_04_t2 ~~ res1*bf05_04_t2 # This allows residual variance on indicator X1 at T2 bf05_09_t2 ~~ res2*bf05_09_t2 # This allows residual variance on indicator X2 at T2 bf05_14_t2 ~~ res3*bf05_14_t2 # This allows residual variance on indicator X3 at T2bf05_19_t2 ~~ res4*bf05_19_t2 # This allows residual variance on indicator X4 at T2bf05_24_t2 ~~ res5*bf05_24_t2 # This allows residual variance on indicator X5 at T2bf05_29_t2 ~~ res6*bf05_29_t2 # This allows residual variance on indicator X6 at T2 bf05_34_t2 ~~ res7*bf05_34_t2 # This allows residual variance on indicator X7 at T2 bf05_39_t2 ~~ res8*bf05_39_t2 # This allows residual variance on indicator X8 at T2bf05_44_t2 ~~ res9*bf05_44_t2 # This allows residual variance on indicator X9 at T2bf05_49_t2 ~~ res10*bf05_49_t2 # This allows residual variance on indicator X10 at T2bf05_54_t2 ~~ res11*bf05_54_t2 # This allows residual variance on indicator X11 at T2bf05_59_t2 ~~ res12*bf05_59_t2 # This allows residual variance on indicator X12 at T2bf05_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_neuro_curr_hyp4 <-lavaan(mi_lcs_neuro_curr_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_curr_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
Correlation of general change goal with neuroticism change score (current-self) is not significantly different from zero, r = 0.034, p = 0.291.
3.6.1.14 Neuroticism - ideal-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_ideal_hyp4 <-'neuro_t1 =~ 1*bf06_04_t1 + lamb2*bf06_09_t1 + lamb3*bf06_14_t1 + lamb4*bf06_19_t1 + lamb5*bf06_24_t1 + lamb6*bf06_29_t1 + lamb7*bf06_34_t1 + lamb8*bf06_39_t1 + lamb9*bf06_44_t1 + lamb10*bf06_49_t1 + lamb11*bf06_54_t1 + lamb12*bf06_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf06_04_t2 + lamb2*bf06_09_t2 + lamb3*bf06_14_t2 + lamb4*bf06_19_t2 + lamb5*bf06_24_t2 + lamb6*bf06_29_t2 + lamb7*bf06_34_t2 + lamb8*bf06_39_t2 + lamb9*bf06_44_t2 + lamb10*bf06_49_t2 + lamb11*bf06_54_t2 + lamb12*bf06_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsneuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf06_04_t1 ~~ bf06_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_09_t1 ~~ bf06_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_14_t1 ~~ bf06_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_19_t1 ~~ bf06_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_24_t1 ~~ bf06_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_29_t1 ~~ bf06_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_34_t1 ~~ bf06_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_39_t1 ~~ bf06_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_44_t1 ~~ bf06_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_49_t1 ~~ bf06_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_54_t1 ~~ bf06_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_59_t1 ~~ bf06_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_04_t1 ~~ res1*bf06_04_t1 # This allows residual variance on indicator X1 at T1 bf06_09_t1 ~~ res2*bf06_09_t1 # This allows residual variance on indicator X2 at T1bf06_14_t1 ~~ res3*bf06_14_t1 # This allows residual variance on indicator X3 at T1bf06_19_t1 ~~ res4*bf06_19_t1 # This allows residual variance on indicator X4 at T1bf06_24_t1 ~~ res5*bf06_24_t1 # This allows residual variance on indicator X5 at T1bf06_29_t1 ~~ res6*bf06_29_t1 # This allows residual variance on indicator X6 at T1 bf06_34_t1 ~~ res7*bf06_34_t1 # This allows residual variance on indicator X7 at T1bf06_39_t1 ~~ res8*bf06_39_t1 # This allows residual variance on indicator X8 at T1bf06_44_t1 ~~ res9*bf06_44_t1 # This allows residual variance on indicator X9 at T1bf06_49_t1 ~~ res10*bf06_49_t1 # This allows residual variance on indicator X10 at T1bf06_54_t1 ~~ res11*bf06_54_t1 # This allows residual variance on indicator X11 at T1bf06_59_t1 ~~ res12*bf06_59_t1 # This allows residual variance on indicator X12 at T1bf06_04_t2 ~~ res1*bf06_04_t2 # This allows residual variance on indicator X1 at T2 bf06_09_t2 ~~ res2*bf06_09_t2 # This allows residual variance on indicator X2 at T2 bf06_14_t2 ~~ res3*bf06_14_t2 # This allows residual variance on indicator X3 at T2bf06_19_t2 ~~ res4*bf06_19_t2 # This allows residual variance on indicator X4 at T2bf06_24_t2 ~~ res5*bf06_24_t2 # This allows residual variance on indicator X5 at T2bf06_29_t2 ~~ res6*bf06_29_t2 # This allows residual variance on indicator X6 at T2 bf06_34_t2 ~~ res7*bf06_34_t2 # This allows residual variance on indicator X7 at T2 bf06_39_t2 ~~ res8*bf06_39_t2 # This allows residual variance on indicator X8 at T2bf06_44_t2 ~~ res9*bf06_44_t2 # This allows residual variance on indicator X9 at T2bf06_49_t2 ~~ res10*bf06_49_t2 # This allows residual variance on indicator X10 at T2bf06_54_t2 ~~ res11*bf06_54_t2 # This allows residual variance on indicator X11 at T2bf06_59_t2 ~~ res12*bf06_59_t2 # This allows residual variance on indicator X12 at T2bf06_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_neuro_ideal_hyp4 <-lavaan(mi_lcs_neuro_ideal_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_ideal_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_curr_specif_hyp4 <-'neuro_t1 =~ 1*bf05_04_t1 + lamb2*bf05_09_t1 + lamb3*bf05_14_t1 + lamb4*bf05_19_t1 + lamb5*bf05_24_t1 + lamb6*bf05_29_t1 + lamb7*bf05_34_t1 + lamb8*bf05_39_t1 + lamb9*bf05_44_t1 + lamb10*bf05_49_t1 + lamb11*bf05_54_t1 + lamb12*bf05_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf05_04_t2 + lamb2*bf05_09_t2 + lamb3*bf05_14_t2 + lamb4*bf05_19_t2 + lamb5*bf05_24_t2 + lamb6*bf05_29_t2 + lamb7*bf05_34_t2 + lamb8*bf05_39_t2 + lamb9*bf05_44_t2 + lamb10*bf05_49_t2 + lamb11*bf05_54_t2 + lamb12*bf05_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_10_t1 + sb07_11_t1 + sb07_12_t1 # latent change goal variable (three facets per trait)neuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf05_04_t1 ~~ bf05_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_09_t1 ~~ bf05_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_14_t1 ~~ bf05_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_19_t1 ~~ bf05_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_24_t1 ~~ bf05_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_29_t1 ~~ bf05_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_34_t1 ~~ bf05_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_39_t1 ~~ bf05_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_44_t1 ~~ bf05_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_49_t1 ~~ bf05_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_54_t1 ~~ bf05_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_59_t1 ~~ bf05_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_04_t1 ~~ res1*bf05_04_t1 # This allows residual variance on indicator X1 at T1 bf05_09_t1 ~~ res2*bf05_09_t1 # This allows residual variance on indicator X2 at T1bf05_14_t1 ~~ res3*bf05_14_t1 # This allows residual variance on indicator X3 at T1bf05_19_t1 ~~ res4*bf05_19_t1 # This allows residual variance on indicator X4 at T1bf05_24_t1 ~~ res5*bf05_24_t1 # This allows residual variance on indicator X5 at T1bf05_29_t1 ~~ res6*bf05_29_t1 # This allows residual variance on indicator X6 at T1 bf05_34_t1 ~~ res7*bf05_34_t1 # This allows residual variance on indicator X7 at T1bf05_39_t1 ~~ res8*bf05_39_t1 # This allows residual variance on indicator X8 at T1bf05_44_t1 ~~ res9*bf05_44_t1 # This allows residual variance on indicator X9 at T1bf05_49_t1 ~~ res10*bf05_49_t1 # This allows residual variance on indicator X10 at T1bf05_54_t1 ~~ res11*bf05_54_t1 # This allows residual variance on indicator X11 at T1bf05_59_t1 ~~ res12*bf05_59_t1 # This allows residual variance on indicator X12 at T1bf05_04_t2 ~~ res1*bf05_04_t2 # This allows residual variance on indicator X1 at T2 bf05_09_t2 ~~ res2*bf05_09_t2 # This allows residual variance on indicator X2 at T2 bf05_14_t2 ~~ res3*bf05_14_t2 # This allows residual variance on indicator X3 at T2bf05_19_t2 ~~ res4*bf05_19_t2 # This allows residual variance on indicator X4 at T2bf05_24_t2 ~~ res5*bf05_24_t2 # This allows residual variance on indicator X5 at T2bf05_29_t2 ~~ res6*bf05_29_t2 # This allows residual variance on indicator X6 at T2 bf05_34_t2 ~~ res7*bf05_34_t2 # This allows residual variance on indicator X7 at T2 bf05_39_t2 ~~ res8*bf05_39_t2 # This allows residual variance on indicator X8 at T2bf05_44_t2 ~~ res9*bf05_44_t2 # This allows residual variance on indicator X9 at T2bf05_49_t2 ~~ res10*bf05_49_t2 # This allows residual variance on indicator X10 at T2bf05_54_t2 ~~ res11*bf05_54_t2 # This allows residual variance on indicator X11 at T2bf05_59_t2 ~~ res12*bf05_59_t2 # This allows residual variance on indicator X12 at T2bf05_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_10_t1 ~~ sb07_10_t1sb07_11_t1 ~~ sb07_11_t1sb07_12_t1 ~~ sb07_12_t1sb07_10_t1 ~ 1sb07_11_t1 ~ 1sb07_12_t1 ~ 1'fit_mi_lcs_neuro_curr_specif_hyp4 <-lavaan(mi_lcs_neuro_curr_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_curr_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
The correlation of specific, facet-level change goals with neuroticism change score (current-self) is significantly different from zero, r = -0.118, p = 0.031.
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_ideal_specif_hyp4 <-'neuro_t1 =~ 1*bf06_04_t1 + lamb2*bf06_09_t1 + lamb3*bf06_14_t1 + lamb4*bf06_19_t1 + lamb5*bf06_24_t1 + lamb6*bf06_29_t1 + lamb7*bf06_34_t1 + lamb8*bf06_39_t1 + lamb9*bf06_44_t1 + lamb10*bf06_49_t1 + lamb11*bf06_54_t1 + lamb12*bf06_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf06_04_t2 + lamb2*bf06_09_t2 + lamb3*bf06_14_t2 + lamb4*bf06_19_t2 + lamb5*bf06_24_t2 + lamb6*bf06_29_t2 + lamb7*bf06_34_t2 + lamb8*bf06_39_t2 + lamb9*bf06_44_t2 + lamb10*bf06_49_t2 + lamb11*bf06_54_t2 + lamb12*bf06_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_10_t1 + sb07_11_t1 + sb07_12_t1 # latent change goal variable (three facets per trait)neuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf06_04_t1 ~~ bf06_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_09_t1 ~~ bf06_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_14_t1 ~~ bf06_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_19_t1 ~~ bf06_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_24_t1 ~~ bf06_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_29_t1 ~~ bf06_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_34_t1 ~~ bf06_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_39_t1 ~~ bf06_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_44_t1 ~~ bf06_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_49_t1 ~~ bf06_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_54_t1 ~~ bf06_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_59_t1 ~~ bf06_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_04_t1 ~~ res1*bf06_04_t1 # This allows residual variance on indicator X1 at T1 bf06_09_t1 ~~ res2*bf06_09_t1 # This allows residual variance on indicator X2 at T1bf06_14_t1 ~~ res3*bf06_14_t1 # This allows residual variance on indicator X3 at T1bf06_19_t1 ~~ res4*bf06_19_t1 # This allows residual variance on indicator X4 at T1bf06_24_t1 ~~ res5*bf06_24_t1 # This allows residual variance on indicator X5 at T1bf06_29_t1 ~~ res6*bf06_29_t1 # This allows residual variance on indicator X6 at T1 bf06_34_t1 ~~ res7*bf06_34_t1 # This allows residual variance on indicator X7 at T1bf06_39_t1 ~~ res8*bf06_39_t1 # This allows residual variance on indicator X8 at T1bf06_44_t1 ~~ res9*bf06_44_t1 # This allows residual variance on indicator X9 at T1bf06_49_t1 ~~ res10*bf06_49_t1 # This allows residual variance on indicator X10 at T1bf06_54_t1 ~~ res11*bf06_54_t1 # This allows residual variance on indicator X11 at T1bf06_59_t1 ~~ res12*bf06_59_t1 # This allows residual variance on indicator X12 at T1bf06_04_t2 ~~ res1*bf06_04_t2 # This allows residual variance on indicator X1 at T2 bf06_09_t2 ~~ res2*bf06_09_t2 # This allows residual variance on indicator X2 at T2 bf06_14_t2 ~~ res3*bf06_14_t2 # This allows residual variance on indicator X3 at T2bf06_19_t2 ~~ res4*bf06_19_t2 # This allows residual variance on indicator X4 at T2bf06_24_t2 ~~ res5*bf06_24_t2 # This allows residual variance on indicator X5 at T2bf06_29_t2 ~~ res6*bf06_29_t2 # This allows residual variance on indicator X6 at T2 bf06_34_t2 ~~ res7*bf06_34_t2 # This allows residual variance on indicator X7 at T2 bf06_39_t2 ~~ res8*bf06_39_t2 # This allows residual variance on indicator X8 at T2bf06_44_t2 ~~ res9*bf06_44_t2 # This allows residual variance on indicator X9 at T2bf06_49_t2 ~~ res10*bf06_49_t2 # This allows residual variance on indicator X10 at T2bf06_54_t2 ~~ res11*bf06_54_t2 # This allows residual variance on indicator X11 at T2bf06_59_t2 ~~ res12*bf06_59_t2 # This allows residual variance on indicator X12 at T2bf06_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_10_t1 ~~ sb07_10_t1sb07_11_t1 ~~ sb07_11_t1sb07_12_t1 ~~ sb07_12_t1sb07_10_t1 ~ 1sb07_11_t1 ~ 1sb07_12_t1 ~ 1'fit_mi_lcs_neuro_ideal_specif_hyp4 <-lavaan(mi_lcs_neuro_ideal_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_ideal_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with neuroticism change score (ideal-self) is not significantly different from zero, r = -0.008, p = 0.732.
3.6.1.17 Openness - current-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_curr_hyp4 <-'openn_t1 =~ 1*bf05_05_t1 + lamb2*bf05_10_t1 + lamb3*bf05_15_t1 + lamb4*bf05_20_t1 + lamb5*bf05_25_t1 + lamb6*bf05_30_t1 + lamb7*bf05_35_t1 + lamb8*bf05_40_t1 + lamb9*bf05_45_t1 + lamb10*bf05_50_t1 + lamb11*bf05_55_t1 + lamb12*bf05_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf05_05_t2 + lamb2*bf05_10_t2 + lamb3*bf05_15_t2 + lamb4*bf05_20_t2 + lamb5*bf05_25_t2 + lamb6*bf05_30_t2 + lamb7*bf05_35_t2 + lamb8*bf05_40_t2 + lamb9*bf05_45_t2 + lamb10*bf05_50_t2 + lamb11*bf05_55_t2 + lamb12*bf05_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsopenn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf05_05_t1 ~~ bf05_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_10_t1 ~~ bf05_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_15_t1 ~~ bf05_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_20_t1 ~~ bf05_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_25_t1 ~~ bf05_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_30_t1 ~~ bf05_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_35_t1 ~~ bf05_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_40_t1 ~~ bf05_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_45_t1 ~~ bf05_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_50_t1 ~~ bf05_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_55_t1 ~~ bf05_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_60_t1 ~~ bf05_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_05_t1 ~~ res1*bf05_05_t1 # This allows residual variance on indicator X1 at T1 bf05_10_t1 ~~ res2*bf05_10_t1 # This allows residual variance on indicator X2 at T1bf05_15_t1 ~~ res3*bf05_15_t1 # This allows residual variance on indicator X3 at T1bf05_20_t1 ~~ res4*bf05_20_t1 # This allows residual variance on indicator X4 at T1bf05_25_t1 ~~ res5*bf05_25_t1 # This allows residual variance on indicator X5 at T1bf05_30_t1 ~~ res6*bf05_30_t1 # This allows residual variance on indicator X6 at T1 bf05_35_t1 ~~ res7*bf05_35_t1 # This allows residual variance on indicator X7 at T1bf05_40_t1 ~~ res8*bf05_40_t1 # This allows residual variance on indicator X8 at T1bf05_45_t1 ~~ res9*bf05_45_t1 # This allows residual variance on indicator X9 at T1bf05_50_t1 ~~ res10*bf05_50_t1 # This allows residual variance on indicator X10 at T1bf05_55_t1 ~~ res11*bf05_55_t1 # This allows residual variance on indicator X11 at T1bf05_60_t1 ~~ res12*bf05_60_t1 # This allows residual variance on indicator X12 at T1bf05_05_t2 ~~ res1*bf05_05_t2 # This allows residual variance on indicator X1 at T2 bf05_10_t2 ~~ res2*bf05_10_t2 # This allows residual variance on indicator X2 at T2 bf05_15_t2 ~~ res3*bf05_15_t2 # This allows residual variance on indicator X3 at T2bf05_20_t2 ~~ res4*bf05_20_t2 # This allows residual variance on indicator X4 at T2bf05_25_t2 ~~ res5*bf05_25_t2 # This allows residual variance on indicator X5 at T2bf05_30_t2 ~~ res6*bf05_30_t2 # This allows residual variance on indicator X6 at T2 bf05_35_t2 ~~ res7*bf05_35_t2 # This allows residual variance on indicator X7 at T2 bf05_40_t2 ~~ res8*bf05_40_t2 # This allows residual variance on indicator X8 at T2bf05_45_t2 ~~ res9*bf05_45_t2 # This allows residual variance on indicator X9 at T2bf05_50_t2 ~~ res10*bf05_50_t2 # This allows residual variance on indicator X10 at T2bf05_55_t2 ~~ res11*bf05_55_t2 # This allows residual variance on indicator X11 at T2bf05_60_t2 ~~ res12*bf05_60_t2 # This allows residual variance on indicator X12 at T2bf05_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_openn_curr_hyp4 <-lavaan(mi_lcs_openn_curr_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_curr_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
Correlation of general change goal with openness change score (current-self) is not significantly different from zero, r = -0.001, p = 0.6.
3.6.1.18 Openness - ideal-self: general change goals
Fit model:
Show the code
# adding correlation with manifest change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_ideal_hyp4 <-'openn_t1 =~ 1*bf06_05_t1 + lamb2*bf06_10_t1 + lamb3*bf06_15_t1 + lamb4*bf06_20_t1 + lamb5*bf06_25_t1 + lamb6*bf06_30_t1 + lamb7*bf06_35_t1 + lamb8*bf06_40_t1 + lamb9*bf06_45_t1 + lamb10*bf06_50_t1 + lamb11*bf06_55_t1 + lamb12*bf06_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf06_05_t2 + lamb2*bf06_10_t2 + lamb3*bf06_15_t2 + lamb4*bf06_20_t2 + lamb5*bf06_25_t2 + lamb6*bf06_30_t2 + lamb7*bf06_35_t2 + lamb8*bf06_40_t2 + lamb9*bf06_45_t2 + lamb10*bf06_50_t2 + lamb11*bf06_55_t2 + lamb12*bf06_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsopenn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ sb06_01_t1 # estimates the covariance/correlation with change goal variablebf06_05_t1 ~~ bf06_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_10_t1 ~~ bf06_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_15_t1 ~~ bf06_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_20_t1 ~~ bf06_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_25_t1 ~~ bf06_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_30_t1 ~~ bf06_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_35_t1 ~~ bf06_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_40_t1 ~~ bf06_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_45_t1 ~~ bf06_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_50_t1 ~~ bf06_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_55_t1 ~~ bf06_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_60_t1 ~~ bf06_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_05_t1 ~~ res1*bf06_05_t1 # This allows residual variance on indicator X1 at T1 bf06_10_t1 ~~ res2*bf06_10_t1 # This allows residual variance on indicator X2 at T1bf06_15_t1 ~~ res3*bf06_15_t1 # This allows residual variance on indicator X3 at T1bf06_20_t1 ~~ res4*bf06_20_t1 # This allows residual variance on indicator X4 at T1bf06_25_t1 ~~ res5*bf06_25_t1 # This allows residual variance on indicator X5 at T1bf06_30_t1 ~~ res6*bf06_30_t1 # This allows residual variance on indicator X6 at T1 bf06_35_t1 ~~ res7*bf06_35_t1 # This allows residual variance on indicator X7 at T1bf06_40_t1 ~~ res8*bf06_40_t1 # This allows residual variance on indicator X8 at T1bf06_45_t1 ~~ res9*bf06_45_t1 # This allows residual variance on indicator X9 at T1bf06_50_t1 ~~ res10*bf06_50_t1 # This allows residual variance on indicator X10 at T1bf06_55_t1 ~~ res11*bf06_55_t1 # This allows residual variance on indicator X11 at T1bf06_60_t1 ~~ res12*bf06_60_t1 # This allows residual variance on indicator X12 at T1bf06_05_t2 ~~ res1*bf06_05_t2 # This allows residual variance on indicator X1 at T2 bf06_10_t2 ~~ res2*bf06_10_t2 # This allows residual variance on indicator X2 at T2 bf06_15_t2 ~~ res3*bf06_15_t2 # This allows residual variance on indicator X3 at T2bf06_20_t2 ~~ res4*bf06_20_t2 # This allows residual variance on indicator X4 at T2bf06_25_t2 ~~ res5*bf06_25_t2 # This allows residual variance on indicator X5 at T2bf06_30_t2 ~~ res6*bf06_30_t2 # This allows residual variance on indicator X6 at T2 bf06_35_t2 ~~ res7*bf06_35_t2 # This allows residual variance on indicator X7 at T2 bf06_40_t2 ~~ res8*bf06_40_t2 # This allows residual variance on indicator X8 at T2bf06_45_t2 ~~ res9*bf06_45_t2 # This allows residual variance on indicator X9 at T2bf06_50_t2 ~~ res10*bf06_50_t2 # This allows residual variance on indicator X10 at T2bf06_55_t2 ~~ res11*bf06_55_t2 # This allows residual variance on indicator X11 at T2bf06_60_t2 ~~ res12*bf06_60_t2 # This allows residual variance on indicator X12 at T2bf06_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb06_01_t1 ~~ sb06_01_t1sb06_01_t1 ~ 1'fit_mi_lcs_openn_ideal_hyp4 <-lavaan(mi_lcs_openn_ideal_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_ideal_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sb06_01_t1 = general change goal):
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_curr_specif_hyp4 <-'openn_t1 =~ 1*bf05_05_t1 + lamb2*bf05_10_t1 + lamb3*bf05_15_t1 + lamb4*bf05_20_t1 + lamb5*bf05_25_t1 + lamb6*bf05_30_t1 + lamb7*bf05_35_t1 + lamb8*bf05_40_t1 + lamb9*bf05_45_t1 + lamb10*bf05_50_t1 + lamb11*bf05_55_t1 + lamb12*bf05_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf05_05_t2 + lamb2*bf05_10_t2 + lamb3*bf05_15_t2 + lamb4*bf05_20_t2 + lamb5*bf05_25_t2 + lamb6*bf05_30_t2 + lamb7*bf05_35_t2 + lamb8*bf05_40_t2 + lamb9*bf05_45_t2 + lamb10*bf05_50_t2 + lamb11*bf05_55_t2 + lamb12*bf05_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_13_t1 + sb07_14_t1 + sb07_15_t1 # latent change goal variable (three facets per trait)openn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf05_05_t1 ~~ bf05_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_10_t1 ~~ bf05_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_15_t1 ~~ bf05_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_20_t1 ~~ bf05_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_25_t1 ~~ bf05_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_30_t1 ~~ bf05_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_35_t1 ~~ bf05_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_40_t1 ~~ bf05_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_45_t1 ~~ bf05_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_50_t1 ~~ bf05_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_55_t1 ~~ bf05_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_60_t1 ~~ bf05_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_05_t1 ~~ res1*bf05_05_t1 # This allows residual variance on indicator X1 at T1 bf05_10_t1 ~~ res2*bf05_10_t1 # This allows residual variance on indicator X2 at T1bf05_15_t1 ~~ res3*bf05_15_t1 # This allows residual variance on indicator X3 at T1bf05_20_t1 ~~ res4*bf05_20_t1 # This allows residual variance on indicator X4 at T1bf05_25_t1 ~~ res5*bf05_25_t1 # This allows residual variance on indicator X5 at T1bf05_30_t1 ~~ res6*bf05_30_t1 # This allows residual variance on indicator X6 at T1 bf05_35_t1 ~~ res7*bf05_35_t1 # This allows residual variance on indicator X7 at T1bf05_40_t1 ~~ res8*bf05_40_t1 # This allows residual variance on indicator X8 at T1bf05_45_t1 ~~ res9*bf05_45_t1 # This allows residual variance on indicator X9 at T1bf05_50_t1 ~~ res10*bf05_50_t1 # This allows residual variance on indicator X10 at T1bf05_55_t1 ~~ res11*bf05_55_t1 # This allows residual variance on indicator X11 at T1bf05_60_t1 ~~ res12*bf05_60_t1 # This allows residual variance on indicator X12 at T1bf05_05_t2 ~~ res1*bf05_05_t2 # This allows residual variance on indicator X1 at T2 bf05_10_t2 ~~ res2*bf05_10_t2 # This allows residual variance on indicator X2 at T2 bf05_15_t2 ~~ res3*bf05_15_t2 # This allows residual variance on indicator X3 at T2bf05_20_t2 ~~ res4*bf05_20_t2 # This allows residual variance on indicator X4 at T2bf05_25_t2 ~~ res5*bf05_25_t2 # This allows residual variance on indicator X5 at T2bf05_30_t2 ~~ res6*bf05_30_t2 # This allows residual variance on indicator X6 at T2 bf05_35_t2 ~~ res7*bf05_35_t2 # This allows residual variance on indicator X7 at T2 bf05_40_t2 ~~ res8*bf05_40_t2 # This allows residual variance on indicator X8 at T2bf05_45_t2 ~~ res9*bf05_45_t2 # This allows residual variance on indicator X9 at T2bf05_50_t2 ~~ res10*bf05_50_t2 # This allows residual variance on indicator X10 at T2bf05_55_t2 ~~ res11*bf05_55_t2 # This allows residual variance on indicator X11 at T2bf05_60_t2 ~~ res12*bf05_60_t2 # This allows residual variance on indicator X12 at T2bf05_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_13_t1 ~~ sb07_13_t1sb07_14_t1 ~~ sb07_14_t1sb07_15_t1 ~~ sb07_15_t1sb07_13_t1 ~ 1sb07_14_t1 ~ 1sb07_15_t1 ~ 1'fit_mi_lcs_openn_curr_specif_hyp4 <-lavaan(mi_lcs_openn_curr_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_curr_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with openness change score (current-self) is not significantly different from zero, r = 0.005, p = 0.43.
# adding correlation with latent (made up of the three facets) change goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_ideal_specif_hyp4 <-'openn_t1 =~ 1*bf06_05_t1 + lamb2*bf06_10_t1 + lamb3*bf06_15_t1 + lamb4*bf06_20_t1 + lamb5*bf06_25_t1 + lamb6*bf06_30_t1 + lamb7*bf06_35_t1 + lamb8*bf06_40_t1 + lamb9*bf06_45_t1 + lamb10*bf06_50_t1 + lamb11*bf06_55_t1 + lamb12*bf06_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf06_05_t2 + lamb2*bf06_10_t2 + lamb3*bf06_15_t2 + lamb4*bf06_20_t2 + lamb5*bf06_25_t2 + lamb6*bf06_30_t2 + lamb7*bf06_35_t2 + lamb8*bf06_40_t2 + lamb9*bf06_45_t2 + lamb10*bf06_50_t2 + lamb11*bf06_55_t2 + lamb12*bf06_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsgoals =~ 1*sb07_13_t1 + sb07_14_t1 + sb07_15_t1 # latent change goal variable (three facets per trait)openn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ goals # estimates the covariance/correlation with the (latent) change goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) change goal variable to 0goals ~~ goals # This estimates the variance of the (latent) change goal variablebf06_05_t1 ~~ bf06_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_10_t1 ~~ bf06_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_15_t1 ~~ bf06_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_20_t1 ~~ bf06_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_25_t1 ~~ bf06_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_30_t1 ~~ bf06_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_35_t1 ~~ bf06_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_40_t1 ~~ bf06_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_45_t1 ~~ bf06_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_50_t1 ~~ bf06_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_55_t1 ~~ bf06_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_60_t1 ~~ bf06_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_05_t1 ~~ res1*bf06_05_t1 # This allows residual variance on indicator X1 at T1 bf06_10_t1 ~~ res2*bf06_10_t1 # This allows residual variance on indicator X2 at T1bf06_15_t1 ~~ res3*bf06_15_t1 # This allows residual variance on indicator X3 at T1bf06_20_t1 ~~ res4*bf06_20_t1 # This allows residual variance on indicator X4 at T1bf06_25_t1 ~~ res5*bf06_25_t1 # This allows residual variance on indicator X5 at T1bf06_30_t1 ~~ res6*bf06_30_t1 # This allows residual variance on indicator X6 at T1 bf06_35_t1 ~~ res7*bf06_35_t1 # This allows residual variance on indicator X7 at T1bf06_40_t1 ~~ res8*bf06_40_t1 # This allows residual variance on indicator X8 at T1bf06_45_t1 ~~ res9*bf06_45_t1 # This allows residual variance on indicator X9 at T1bf06_50_t1 ~~ res10*bf06_50_t1 # This allows residual variance on indicator X10 at T1bf06_55_t1 ~~ res11*bf06_55_t1 # This allows residual variance on indicator X11 at T1bf06_60_t1 ~~ res12*bf06_60_t1 # This allows residual variance on indicator X12 at T1bf06_05_t2 ~~ res1*bf06_05_t2 # This allows residual variance on indicator X1 at T2 bf06_10_t2 ~~ res2*bf06_10_t2 # This allows residual variance on indicator X2 at T2 bf06_15_t2 ~~ res3*bf06_15_t2 # This allows residual variance on indicator X3 at T2bf06_20_t2 ~~ res4*bf06_20_t2 # This allows residual variance on indicator X4 at T2bf06_25_t2 ~~ res5*bf06_25_t2 # This allows residual variance on indicator X5 at T2bf06_30_t2 ~~ res6*bf06_30_t2 # This allows residual variance on indicator X6 at T2 bf06_35_t2 ~~ res7*bf06_35_t2 # This allows residual variance on indicator X7 at T2 bf06_40_t2 ~~ res8*bf06_40_t2 # This allows residual variance on indicator X8 at T2bf06_45_t2 ~~ res9*bf06_45_t2 # This allows residual variance on indicator X9 at T2bf06_50_t2 ~~ res10*bf06_50_t2 # This allows residual variance on indicator X10 at T2bf06_55_t2 ~~ res11*bf06_55_t2 # This allows residual variance on indicator X11 at T2bf06_60_t2 ~~ res12*bf06_60_t2 # This allows residual variance on indicator X12 at T2bf06_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb07_13_t1 ~~ sb07_13_t1sb07_14_t1 ~~ sb07_14_t1sb07_15_t1 ~~ sb07_15_t1sb07_13_t1 ~ 1sb07_14_t1 ~ 1sb07_15_t1 ~ 1'fit_mi_lcs_openn_ideal_specif_hyp4 <-lavaan(mi_lcs_openn_ideal_specif_hyp4, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_ideal_specif_hyp4, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific change goal):
Correlation of specific, facet-level change goals with openness change score (ideal-self) is not significantly different from zero, r = 0.004, p = 0.45.
3.6.2 Big Five facets
Run models for all facets with a template & loop:
Show the code
# create template:facet_template <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)facet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 d_facet_1 ~ facet_t1 # This estimates the self-feedback parameterd_facet_1 ~~ ind_goal # estimates the covariance/correlation with change goal variableind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind_goal ~~ ind_goalind_goal ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# loop across 2 BFI versions (combined pre&post current/ideal)for (j in5:length(bfi_versions)) { items =paste0(bfi_versions[[j]], item_nrs)# loop across 2 different goal operationalizations (sb06_01_t1 & sb07_XX_t1)for (k in1:2) {if (k==1) { goal_op ="sb06_01_t1" } else{ goal_op =paste0("sb07_", str_pad(i-5, 2, pad ="0"), "_t1") } template_filled <-str_replace_all(facet_template, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4],"ind_goal"= goal_op)) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sb, estimator='mlr', fixed.x=FALSE, missing='fiml')# save to environmentif (k==1) {eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_hyp4")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_hyp4")), facet_model_fit)) } else{eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_specif_hyp4")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_specif_hyp4")), facet_model_fit)) } } }}
3.6.2.1 Sociability - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with sociability change score (current-self) is not significantly different from zero, r = -0.051, p = 0.29.
Correlation of specific, facet-level change goals with anxiety change score (ideal-self) is not significantly different from zero, r = 0.059, p = 0.057.
3.6.2.5 Assertiveness - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with assertiveness change score (current-self) is not significantly different from zero, r = 0.008, p = 0.825.
Correlation of specific, facet-level change goals with assertiveness change score (ideal-self) is not significantly different from zero, r = 0.011, p = 0.633.
3.6.2.9 Energy - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with energy change score (current-self) is not significantly different from zero, r = 0.024, p = 0.327.
3.6.2.12 Energy - ideal-self: specific, facet-level change goals
Results summary (*sb07_$$_t1* = trait/facet specific change goal):
Correlation of specific, facet-level change goals with energy change score (ideal-self) is not significantly different from zero, r = 0.026, p = 0.424.
3.6.2.13 Compassion - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with compassion change score (current-self) is not significantly different from zero, r = -0.013, p = 0.767.
Correlation of specific, facet-level change goals with compassion change score (ideal-self) is not significantly different from zero, r = -0.054, p = 0.373.
3.6.2.17 Respectfulness - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with respectfulness change score (current-self) is not significantly different from zero, r = 0.019, p = 0.644.
The correlation of specific, facet-level change goals with the respectfulness change score (ideal-self) is significantly different from zero, r = -0.071, p = 0.043.
3.6.2.21 Trust - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with trust change score (current-self) is not significantly different from zero, r = -0.031, p = 0.486.
Correlation of specific, facet-level change goals with organization change score (current-self) is not significantly different from zero, r = 0.063, p = 0.377.
Correlation of specific, facet-level change goals with organization change score (ideal-self) is not significantly different from zero, r = 0.059, p = 0.138.
3.6.2.29 Productiveness - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with productiveness change score (current-self) is not significantly different from zero, r = 0.023, p = 0.598.
Correlation of specific, facet-level change goals with productiveness change score (ideal-self) is not significantly different from zero, r = 0.025, p = 0.377.
3.6.2.33 Responsibility - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with responsibility change score (current-self) is not significantly different from zero, r = -0.045, p = 0.2.
Correlation of specific, facet-level change goals with responsibility change score (ideal-self) is not significantly different from zero, r = -0.016, p = 0.718.
3.6.2.37 Anxiety - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
The correlation of specific, facet-level change goals with the anxiety change score (current-self) is significantly different from zero, r = -0.219, p = 0.006.
Correlation of specific, facet-level change goals with anxiety change score (ideal-self) is not significantly different from zero, r = 0.019, p = 0.391.
3.6.2.41 Depression - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with depression change score (current-self) is not significantly different from zero, r = -0.181, p = 0.007.
The correlation of specific, facet-level change goals with the depression change score (ideal-self) is significantly different from zero, r = -0.059, p = 0.118.
3.6.2.45 Volatility - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with volatility change score (current-self) is not significantly different from zero, r = -0.009, p = 0.863.
Correlation of specific, facet-level change goals with volatility change score (ideal-self) is not significantly different from zero, r = -0.02, p = 0.607.
3.6.2.49 Curiosity - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with curiosity change score (current-self) is not significantly different from zero, r = -0.027, p = 0.456.
Correlation of specific, facet-level change goals with curiosity change score (ideal-self) is not significantly different from zero, r = 0.012, p = 0.723.
3.6.2.53 Aesthetic - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with aesthetic change score (current-self) is not significantly different from zero, r = 0.006, p = 0.053.
Correlation of specific, facet-level change goals with aesthetic change score (ideal-self) is not significantly different from zero, r = 0.022, p = 0.156.
3.6.2.57 Imagination - current-self: general change goals
Results summary (sb06_01_t1 = general change goal):
Correlation of specific, facet-level change goals with imagination change score (current-self) is not significantly different from zero, r = 0.033, p = 0.494.
Correlation of specific, facet-level change goals with imagination change score (ideal-self) is not significantly different from zero, r = -0.026, p = 0.55.
Results summary across the Big Five traits: covariance of the latent change score and change goal(s)
kable(df_table_hyp4[1:20, ], digits =3)
trait
ref
goal
estimate
std.all
statistic
p.value
extraversion
current
general
0.073
0.142
1.842
0.065
extraversion
ideal
general
0.036
0.136
1.590
0.112
extraversion
current
specific
0.012
0.041
0.367
0.713
extraversion
ideal
specific
0.012
0.077
0.518
0.604
agreeableness
current
general
-0.007
-0.025
-0.329
0.742
agreeableness
ideal
general
-0.004
-0.013
-0.145
0.885
agreeableness
current
specific
0.018
0.070
0.704
0.481
agreeableness
ideal
specific
-0.040
-0.135
-1.368
0.171
conscientiousness
current
general
-0.022
-0.049
-0.664
0.506
conscientiousness
ideal
general
0.006
0.021
0.262
0.793
conscientiousness
current
specific
0.011
0.021
0.225
0.822
conscientiousness
ideal
specific
0.027
0.086
1.098
0.272
neuroticism
current
general
0.034
0.069
1.055
0.291
neuroticism
ideal
general
0.021
0.081
0.962
0.336
neuroticism
current
specific
-0.118
-0.216
-2.157
0.031
neuroticism
ideal
specific
-0.008
-0.026
-0.342
0.732
openness
current
general
-0.001
-0.045
-0.525
0.600
openness
ideal
general
-0.005
-0.088
-0.721
0.471
openness
current
specific
0.005
0.226
0.790
0.430
openness
ideal
specific
0.004
0.105
0.755
0.450
Only one covariance that significantly differs from zero: changes in current-level neuroticism covary with specific trait goals (latent factor of the three N facets).
Results summary across the Big Five facets: covariance of the latent change score and change goal(s)
kable(df_table_hyp4[21:80, ], digits =3)
trait
ref
goal
estimate
std.all
statistic
p.value
sociability
current
general
0.072
0.145
1.777
0.076
sociability
ideal
general
0.042
0.183
1.517
0.129
sociability
current
specific
-0.051
-0.086
-1.057
0.290
sociability
ideal
specific
0.059
0.215
1.902
0.057
assertiveness
current
general
0.009
0.042
0.298
0.766
assertiveness
ideal
general
0.038
0.198
1.913
0.056
assertiveness
current
specific
0.008
0.030
0.221
0.825
assertiveness
ideal
specific
0.011
0.047
0.478
0.633
energy
current
general
-0.014
-0.063
-0.676
0.499
energy
ideal
general
-0.024
-0.095
-0.947
0.343
energy
current
specific
0.024
0.084
0.979
0.327
energy
ideal
specific
0.026
0.086
0.799
0.424
compassion
current
general
0.023
0.120
0.893
0.372
compassion
ideal
general
0.016
0.042
0.365
0.715
compassion
current
specific
-0.013
-0.049
-0.297
0.767
compassion
ideal
specific
-0.054
-0.101
-0.890
0.373
respectfulness
current
general
-0.037
-0.125
-1.401
0.161
respectfulness
ideal
general
-0.007
-0.027
-0.284
0.776
respectfulness
current
specific
0.019
0.048
0.462
0.644
respectfulness
ideal
specific
-0.071
-0.203
-2.027
0.043
trust
current
general
-0.030
-0.088
-0.933
0.351
trust
ideal
general
0.003
0.012
0.121
0.904
trust
current
specific
-0.031
-0.068
-0.697
0.486
trust
ideal
specific
0.019
0.067
0.645
0.519
organization
current
general
-0.069
-0.143
-1.645
0.100
organization
ideal
general
-0.017
-0.056
-0.589
0.556
organization
current
specific
0.063
0.088
0.883
0.377
organization
ideal
specific
0.059
0.132
1.482
0.138
productiveness
current
general
0.005
0.015
0.183
0.855
productiveness
ideal
general
0.013
0.049
0.506
0.613
productiveness
current
specific
0.023
0.050
0.527
0.598
productiveness
ideal
specific
0.025
0.074
0.883
0.377
responsibility
current
general
-0.044
-0.214
-1.927
0.054
responsibility
ideal
general
0.003
0.010
0.097
0.923
responsibility
current
specific
-0.045
-0.145
-1.281
0.200
responsibility
ideal
specific
-0.016
-0.039
-0.361
0.718
anxiety
current
general
0.053
0.103
1.330
0.184
anxiety
ideal
general
0.009
0.064
0.575
0.566
anxiety
current
specific
-0.219
-0.269
-2.731
0.006
anxiety
ideal
specific
0.019
0.085
0.858
0.391
depression
current
general
0.018
0.048
0.665
0.506
depression
ideal
general
0.033
0.108
1.174
0.240
depression
current
specific
-0.181
-0.295
-2.709
0.007
depression
ideal
specific
-0.059
-0.120
-1.563
0.118
volatility
current
general
0.016
0.035
0.413
0.679
volatility
ideal
general
-0.044
-0.146
-1.397
0.162
volatility
current
specific
-0.009
-0.016
-0.173
0.863
volatility
ideal
specific
-0.020
-0.051
-0.515
0.607
curiosity
current
general
-0.010
-0.060
-0.372
0.710
curiosity
ideal
general
-0.012
-0.144
-0.437
0.662
curiosity
current
specific
-0.027
-0.128
-0.746
0.456
curiosity
ideal
specific
0.012
0.118
0.355
0.723
aesthetic
current
general
-0.001
-0.047
-0.552
0.581
aesthetic
ideal
general
-0.010
-0.102
-0.997
0.319
aesthetic
current
specific
0.006
0.165
1.933
0.053
aesthetic
ideal
specific
0.022
0.171
1.419
0.156
imagination
current
general
0.002
0.005
0.059
0.953
imagination
ideal
general
0.010
0.024
0.298
0.766
imagination
current
specific
0.033
0.061
0.684
0.494
imagination
ideal
specific
-0.026
-0.047
-0.598
0.550
Looking at the facets, we see only three covariances that significantly differ from zero: Matching the effects from neuroticism above, we find that changes in current-level anxiety and depression covary with the respective specific facet change goal. Further, changes in ideal-level respectfulness covary with the specific facet change goal (small effect that is barely significant and in the unexpected direction).
3.7 Hypothesis 5: Acceptance goals and change in personality (current / ideal) in self-acceptance group
In the self-acceptance group, there will be a correlation between acceptance goals and change in ideal-self ratings but not change in current-self ratings.
We will test this one domain/facet at a time. We will use both general continuous change goal score as well as trait-specific change goals. To test this hypothesis, we will estimate the mean-level difference across time for both current and ideal trait ratings using latent change models and correlate change goals with the change variable from those models.
3.7.1.1 Extraversion - current-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_curr_hyp5 <-'extra_t1 =~ 1*bf05_01_t1 + lamb2*bf05_06_t1 + lamb3*bf05_11_t1 + lamb4*bf05_16_t1 + lamb5*bf05_21_t1 + lamb6*bf05_26_t1 + lamb7*bf05_31_t1 + lamb8*bf05_36_t1 + lamb9*bf05_41_t1 + lamb10*bf05_46_t1 + lamb11*bf05_51_t1 + lamb12*bf05_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf05_01_t2 + lamb2*bf05_06_t2 + lamb3*bf05_11_t2 + lamb4*bf05_16_t2 + lamb5*bf05_21_t2 + lamb6*bf05_26_t2 + lamb7*bf05_31_t2 + lamb8*bf05_36_t2 + lamb9*bf05_41_t2 + lamb10*bf05_46_t2 + lamb11*bf05_51_t2 + lamb12*bf05_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsextra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf05_01_t1 ~~ bf05_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_06_t1 ~~ bf05_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_11_t1 ~~ bf05_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_16_t1 ~~ bf05_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_21_t1 ~~ bf05_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_26_t1 ~~ bf05_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_31_t1 ~~ bf05_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_36_t1 ~~ bf05_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_41_t1 ~~ bf05_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_46_t1 ~~ bf05_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_51_t1 ~~ bf05_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_56_t1 ~~ bf05_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_01_t1 ~~ res1*bf05_01_t1 # This allows residual variance on indicator X1 at T1 bf05_06_t1 ~~ res2*bf05_06_t1 # This allows residual variance on indicator X2 at T1bf05_11_t1 ~~ res3*bf05_11_t1 # This allows residual variance on indicator X3 at T1bf05_16_t1 ~~ res4*bf05_16_t1 # This allows residual variance on indicator X4 at T1bf05_21_t1 ~~ res5*bf05_21_t1 # This allows residual variance on indicator X5 at T1bf05_26_t1 ~~ res6*bf05_26_t1 # This allows residual variance on indicator X6 at T1 bf05_31_t1 ~~ res7*bf05_31_t1 # This allows residual variance on indicator X7 at T1bf05_36_t1 ~~ res8*bf05_36_t1 # This allows residual variance on indicator X8 at T1bf05_41_t1 ~~ res9*bf05_41_t1 # This allows residual variance on indicator X9 at T1bf05_46_t1 ~~ res10*bf05_46_t1 # This allows residual variance on indicator X10 at T1bf05_51_t1 ~~ res11*bf05_51_t1 # This allows residual variance on indicator X11 at T1bf05_56_t1 ~~ res12*bf05_56_t1 # This allows residual variance on indicator X12 at T1bf05_01_t2 ~~ res1*bf05_01_t2 # This allows residual variance on indicator X1 at T2 bf05_06_t2 ~~ res2*bf05_06_t2 # This allows residual variance on indicator X2 at T2 bf05_11_t2 ~~ res3*bf05_11_t2 # This allows residual variance on indicator X3 at T2bf05_16_t2 ~~ res4*bf05_16_t2 # This allows residual variance on indicator X4 at T2bf05_21_t2 ~~ res5*bf05_21_t2 # This allows residual variance on indicator X5 at T2bf05_26_t2 ~~ res6*bf05_26_t2 # This allows residual variance on indicator X6 at T2 bf05_31_t2 ~~ res7*bf05_31_t2 # This allows residual variance on indicator X7 at T2 bf05_36_t2 ~~ res8*bf05_36_t2 # This allows residual variance on indicator X8 at T2bf05_41_t2 ~~ res9*bf05_41_t2 # This allows residual variance on indicator X9 at T2bf05_46_t2 ~~ res10*bf05_46_t2 # This allows residual variance on indicator X10 at T2bf05_51_t2 ~~ res11*bf05_51_t2 # This allows residual variance on indicator X11 at T2bf05_56_t2 ~~ res12*bf05_56_t2 # This allows residual variance on indicator X12 at T2bf05_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_extra_curr_hyp5 <-lavaan(mi_lcs_extra_curr_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_curr_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of general acceptance goal with the extraversion change score (current-self) is significantly different from zero, r = 0.059, p = 0.025.
3.7.1.2 Extraversion - ideal-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_ideal_hyp5 <-'extra_t1 =~ 1*bf06_01_t1 + lamb2*bf06_06_t1 + lamb3*bf06_11_t1 + lamb4*bf06_16_t1 + lamb5*bf06_21_t1 + lamb6*bf06_26_t1 + lamb7*bf06_31_t1 + lamb8*bf06_36_t1 + lamb9*bf06_41_t1 + lamb10*bf06_46_t1 + lamb11*bf06_51_t1 + lamb12*bf06_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf06_01_t2 + lamb2*bf06_06_t2 + lamb3*bf06_11_t2 + lamb4*bf06_16_t2 + lamb5*bf06_21_t2 + lamb6*bf06_26_t2 + lamb7*bf06_31_t2 + lamb8*bf06_36_t2 + lamb9*bf06_41_t2 + lamb10*bf06_46_t2 + lamb11*bf06_51_t2 + lamb12*bf06_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsextra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf06_01_t1 ~~ bf06_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_06_t1 ~~ bf06_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_11_t1 ~~ bf06_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_16_t1 ~~ bf06_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_21_t1 ~~ bf06_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_26_t1 ~~ bf06_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_31_t1 ~~ bf06_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_36_t1 ~~ bf06_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_41_t1 ~~ bf06_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_46_t1 ~~ bf06_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_51_t1 ~~ bf06_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_56_t1 ~~ bf06_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_01_t1 ~~ res1*bf06_01_t1 # This allows residual variance on indicator X1 at T1 bf06_06_t1 ~~ res2*bf06_06_t1 # This allows residual variance on indicator X2 at T1bf06_11_t1 ~~ res3*bf06_11_t1 # This allows residual variance on indicator X3 at T1bf06_16_t1 ~~ res4*bf06_16_t1 # This allows residual variance on indicator X4 at T1bf06_21_t1 ~~ res5*bf06_21_t1 # This allows residual variance on indicator X5 at T1bf06_26_t1 ~~ res6*bf06_26_t1 # This allows residual variance on indicator X6 at T1 bf06_31_t1 ~~ res7*bf06_31_t1 # This allows residual variance on indicator X7 at T1bf06_36_t1 ~~ res8*bf06_36_t1 # This allows residual variance on indicator X8 at T1bf06_41_t1 ~~ res9*bf06_41_t1 # This allows residual variance on indicator X9 at T1bf06_46_t1 ~~ res10*bf06_46_t1 # This allows residual variance on indicator X10 at T1bf06_51_t1 ~~ res11*bf06_51_t1 # This allows residual variance on indicator X11 at T1bf06_56_t1 ~~ res12*bf06_56_t1 # This allows residual variance on indicator X12 at T1bf06_01_t2 ~~ res1*bf06_01_t2 # This allows residual variance on indicator X1 at T2 bf06_06_t2 ~~ res2*bf06_06_t2 # This allows residual variance on indicator X2 at T2 bf06_11_t2 ~~ res3*bf06_11_t2 # This allows residual variance on indicator X3 at T2bf06_16_t2 ~~ res4*bf06_16_t2 # This allows residual variance on indicator X4 at T2bf06_21_t2 ~~ res5*bf06_21_t2 # This allows residual variance on indicator X5 at T2bf06_26_t2 ~~ res6*bf06_26_t2 # This allows residual variance on indicator X6 at T2 bf06_31_t2 ~~ res7*bf06_31_t2 # This allows residual variance on indicator X7 at T2 bf06_36_t2 ~~ res8*bf06_36_t2 # This allows residual variance on indicator X8 at T2bf06_41_t2 ~~ res9*bf06_41_t2 # This allows residual variance on indicator X9 at T2bf06_46_t2 ~~ res10*bf06_46_t2 # This allows residual variance on indicator X10 at T2bf06_51_t2 ~~ res11*bf06_51_t2 # This allows residual variance on indicator X11 at T2bf06_56_t2 ~~ res12*bf06_56_t2 # This allows residual variance on indicator X12 at T2bf06_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_extra_ideal_hyp5 <-lavaan(mi_lcs_extra_ideal_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_ideal_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_curr_specif_hyp5 <-'extra_t1 =~ 1*bf05_01_t1 + lamb2*bf05_06_t1 + lamb3*bf05_11_t1 + lamb4*bf05_16_t1 + lamb5*bf05_21_t1 + lamb6*bf05_26_t1 + lamb7*bf05_31_t1 + lamb8*bf05_36_t1 + lamb9*bf05_41_t1 + lamb10*bf05_46_t1 + lamb11*bf05_51_t1 + lamb12*bf05_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf05_01_t2 + lamb2*bf05_06_t2 + lamb3*bf05_11_t2 + lamb4*bf05_16_t2 + lamb5*bf05_21_t2 + lamb6*bf05_26_t2 + lamb7*bf05_31_t2 + lamb8*bf05_36_t2 + lamb9*bf05_41_t2 + lamb10*bf05_46_t2 + lamb11*bf05_51_t2 + lamb12*bf05_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_01_t1 + sa07_02_t1 + sa07_03_t1 # latent acceptance goal variable (three facets per trait)extra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf05_01_t1 ~~ bf05_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_06_t1 ~~ bf05_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_11_t1 ~~ bf05_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_16_t1 ~~ bf05_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_21_t1 ~~ bf05_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_26_t1 ~~ bf05_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_31_t1 ~~ bf05_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_36_t1 ~~ bf05_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_41_t1 ~~ bf05_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_46_t1 ~~ bf05_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_51_t1 ~~ bf05_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_56_t1 ~~ bf05_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_01_t1 ~~ res1*bf05_01_t1 # This allows residual variance on indicator X1 at T1 bf05_06_t1 ~~ res2*bf05_06_t1 # This allows residual variance on indicator X2 at T1bf05_11_t1 ~~ res3*bf05_11_t1 # This allows residual variance on indicator X3 at T1bf05_16_t1 ~~ res4*bf05_16_t1 # This allows residual variance on indicator X4 at T1bf05_21_t1 ~~ res5*bf05_21_t1 # This allows residual variance on indicator X5 at T1bf05_26_t1 ~~ res6*bf05_26_t1 # This allows residual variance on indicator X6 at T1 bf05_31_t1 ~~ res7*bf05_31_t1 # This allows residual variance on indicator X7 at T1bf05_36_t1 ~~ res8*bf05_36_t1 # This allows residual variance on indicator X8 at T1bf05_41_t1 ~~ res9*bf05_41_t1 # This allows residual variance on indicator X9 at T1bf05_46_t1 ~~ res10*bf05_46_t1 # This allows residual variance on indicator X10 at T1bf05_51_t1 ~~ res11*bf05_51_t1 # This allows residual variance on indicator X11 at T1bf05_56_t1 ~~ res12*bf05_56_t1 # This allows residual variance on indicator X12 at T1bf05_01_t2 ~~ res1*bf05_01_t2 # This allows residual variance on indicator X1 at T2 bf05_06_t2 ~~ res2*bf05_06_t2 # This allows residual variance on indicator X2 at T2 bf05_11_t2 ~~ res3*bf05_11_t2 # This allows residual variance on indicator X3 at T2bf05_16_t2 ~~ res4*bf05_16_t2 # This allows residual variance on indicator X4 at T2bf05_21_t2 ~~ res5*bf05_21_t2 # This allows residual variance on indicator X5 at T2bf05_26_t2 ~~ res6*bf05_26_t2 # This allows residual variance on indicator X6 at T2 bf05_31_t2 ~~ res7*bf05_31_t2 # This allows residual variance on indicator X7 at T2 bf05_36_t2 ~~ res8*bf05_36_t2 # This allows residual variance on indicator X8 at T2bf05_41_t2 ~~ res9*bf05_41_t2 # This allows residual variance on indicator X9 at T2bf05_46_t2 ~~ res10*bf05_46_t2 # This allows residual variance on indicator X10 at T2bf05_51_t2 ~~ res11*bf05_51_t2 # This allows residual variance on indicator X11 at T2bf05_56_t2 ~~ res12*bf05_56_t2 # This allows residual variance on indicator X12 at T2bf05_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_01_t1 ~~ sa07_01_t1sa07_02_t1 ~~ sa07_02_t1sa07_03_t1 ~~ sa07_03_t1sa07_01_t1 ~ 1sa07_02_t1 ~ 1sa07_03_t1 ~ 1'fit_mi_lcs_extra_curr_specif_hyp5 <-lavaan(mi_lcs_extra_curr_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_curr_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with extraversion change score (current-self) is not significantly different from zero, r = 0.041, p = 0.337.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_extra_ideal_specif_hyp5 <-'extra_t1 =~ 1*bf06_01_t1 + lamb2*bf06_06_t1 + lamb3*bf06_11_t1 + lamb4*bf06_16_t1 + lamb5*bf06_21_t1 + lamb6*bf06_26_t1 + lamb7*bf06_31_t1 + lamb8*bf06_36_t1 + lamb9*bf06_41_t1 + lamb10*bf06_46_t1 + lamb11*bf06_51_t1 + lamb12*bf06_56_t1 # This specifies the measurement model for extra_t1 extra_t2 =~ 1*bf06_01_t2 + lamb2*bf06_06_t2 + lamb3*bf06_11_t2 + lamb4*bf06_16_t2 + lamb5*bf06_21_t2 + lamb6*bf06_26_t2 + lamb7*bf06_31_t2 + lamb8*bf06_36_t2 + lamb9*bf06_41_t2 + lamb10*bf06_46_t2 + lamb11*bf06_51_t2 + lamb12*bf06_56_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_01_t1 + sa07_02_t1 + sa07_03_t1 # latent acceptance goal variable (three facets per trait)extra_t2 ~ 1*extra_t1 # This parameter regresses extra_t2 perfectly on extra_t1d_extra_1 =~ 1*extra_t2 # This defines the latent change score factor as measured perfectly by scores on extra_t2extra_t2 ~ 0*1 # This line constrains the intercept of extra_t2 to 0extra_t2 ~~ 0*extra_t2 # This fixes the variance of extra_t2 to 0d_extra_1 ~ 1 # This estimates the intercept of the change score extra_t1 ~ 1 # This estimates the intercept of extra_t1 d_extra_1 ~~ d_extra_1 # This estimates the variance of the change scores extra_t1 ~~ extra_t1 # This estimates the variance of the extra_t1 d_extra_1 ~ extra_t1 # This estimates the self-feedback parameterd_extra_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf06_01_t1 ~~ bf06_01_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_06_t1 ~~ bf06_06_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_11_t1 ~~ bf06_11_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_16_t1 ~~ bf06_16_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_21_t1 ~~ bf06_21_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_26_t1 ~~ bf06_26_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_31_t1 ~~ bf06_31_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_36_t1 ~~ bf06_36_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_41_t1 ~~ bf06_41_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_46_t1 ~~ bf06_46_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_51_t1 ~~ bf06_51_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_56_t1 ~~ bf06_56_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_01_t1 ~~ res1*bf06_01_t1 # This allows residual variance on indicator X1 at T1 bf06_06_t1 ~~ res2*bf06_06_t1 # This allows residual variance on indicator X2 at T1bf06_11_t1 ~~ res3*bf06_11_t1 # This allows residual variance on indicator X3 at T1bf06_16_t1 ~~ res4*bf06_16_t1 # This allows residual variance on indicator X4 at T1bf06_21_t1 ~~ res5*bf06_21_t1 # This allows residual variance on indicator X5 at T1bf06_26_t1 ~~ res6*bf06_26_t1 # This allows residual variance on indicator X6 at T1 bf06_31_t1 ~~ res7*bf06_31_t1 # This allows residual variance on indicator X7 at T1bf06_36_t1 ~~ res8*bf06_36_t1 # This allows residual variance on indicator X8 at T1bf06_41_t1 ~~ res9*bf06_41_t1 # This allows residual variance on indicator X9 at T1bf06_46_t1 ~~ res10*bf06_46_t1 # This allows residual variance on indicator X10 at T1bf06_51_t1 ~~ res11*bf06_51_t1 # This allows residual variance on indicator X11 at T1bf06_56_t1 ~~ res12*bf06_56_t1 # This allows residual variance on indicator X12 at T1bf06_01_t2 ~~ res1*bf06_01_t2 # This allows residual variance on indicator X1 at T2 bf06_06_t2 ~~ res2*bf06_06_t2 # This allows residual variance on indicator X2 at T2 bf06_11_t2 ~~ res3*bf06_11_t2 # This allows residual variance on indicator X3 at T2bf06_16_t2 ~~ res4*bf06_16_t2 # This allows residual variance on indicator X4 at T2bf06_21_t2 ~~ res5*bf06_21_t2 # This allows residual variance on indicator X5 at T2bf06_26_t2 ~~ res6*bf06_26_t2 # This allows residual variance on indicator X6 at T2 bf06_31_t2 ~~ res7*bf06_31_t2 # This allows residual variance on indicator X7 at T2 bf06_36_t2 ~~ res8*bf06_36_t2 # This allows residual variance on indicator X8 at T2bf06_41_t2 ~~ res9*bf06_41_t2 # This allows residual variance on indicator X9 at T2bf06_46_t2 ~~ res10*bf06_46_t2 # This allows residual variance on indicator X10 at T2bf06_51_t2 ~~ res11*bf06_51_t2 # This allows residual variance on indicator X11 at T2bf06_56_t2 ~~ res12*bf06_56_t2 # This allows residual variance on indicator X12 at T2bf06_01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_06_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_11_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_16_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_21_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_26_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_31_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_36_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_41_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_46_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_51_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_56_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_06_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_11_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_16_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_21_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_26_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_31_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_36_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_41_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_46_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_51_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_56_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_01_t1 ~~ sa07_01_t1sa07_02_t1 ~~ sa07_02_t1sa07_03_t1 ~~ sa07_03_t1sa07_01_t1 ~ 1sa07_02_t1 ~ 1sa07_03_t1 ~ 1'fit_mi_lcs_extra_ideal_specif_hyp5 <-lavaan(mi_lcs_extra_ideal_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_extra_ideal_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with extraversion change score (ideal-self) is not significantly different from zero, r = -0.024, p = 0.277.
3.7.1.5 Agreeableness - current-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_curr_hyp5 <-'agree_t1 =~ 1*bf05_02_t1 + lamb2*bf05_07_t1 + lamb3*bf05_12_t1 + lamb4*bf05_17_t1 + lamb5*bf05_22_t1 + lamb6*bf05_27_t1 + lamb7*bf05_32_t1 + lamb8*bf05_37_t1 + lamb9*bf05_42_t1 + lamb10*bf05_47_t1 + lamb11*bf05_52_t1 + lamb12*bf05_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf05_02_t2 + lamb2*bf05_07_t2 + lamb3*bf05_12_t2 + lamb4*bf05_17_t2 + lamb5*bf05_22_t2 + lamb6*bf05_27_t2 + lamb7*bf05_32_t2 + lamb8*bf05_37_t2 + lamb9*bf05_42_t2 + lamb10*bf05_47_t2 + lamb11*bf05_52_t2 + lamb12*bf05_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsagree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf05_02_t1 ~~ bf05_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_07_t1 ~~ bf05_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_12_t1 ~~ bf05_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_17_t1 ~~ bf05_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_22_t1 ~~ bf05_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_27_t1 ~~ bf05_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_32_t1 ~~ bf05_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_37_t1 ~~ bf05_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_42_t1 ~~ bf05_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_47_t1 ~~ bf05_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_52_t1 ~~ bf05_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_57_t1 ~~ bf05_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_02_t1 ~~ res1*bf05_02_t1 # This allows residual variance on indicator X1 at T1 bf05_07_t1 ~~ res2*bf05_07_t1 # This allows residual variance on indicator X2 at T1bf05_12_t1 ~~ res3*bf05_12_t1 # This allows residual variance on indicator X3 at T1bf05_17_t1 ~~ res4*bf05_17_t1 # This allows residual variance on indicator X4 at T1bf05_22_t1 ~~ res5*bf05_22_t1 # This allows residual variance on indicator X5 at T1bf05_27_t1 ~~ res6*bf05_27_t1 # This allows residual variance on indicator X6 at T1 bf05_32_t1 ~~ res7*bf05_32_t1 # This allows residual variance on indicator X7 at T1bf05_37_t1 ~~ res8*bf05_37_t1 # This allows residual variance on indicator X8 at T1bf05_42_t1 ~~ res9*bf05_42_t1 # This allows residual variance on indicator X9 at T1bf05_47_t1 ~~ res10*bf05_47_t1 # This allows residual variance on indicator X10 at T1bf05_52_t1 ~~ res11*bf05_52_t1 # This allows residual variance on indicator X11 at T1bf05_57_t1 ~~ res12*bf05_57_t1 # This allows residual variance on indicator X12 at T1bf05_02_t2 ~~ res1*bf05_02_t2 # This allows residual variance on indicator X1 at T2 bf05_07_t2 ~~ res2*bf05_07_t2 # This allows residual variance on indicator X2 at T2 bf05_12_t2 ~~ res3*bf05_12_t2 # This allows residual variance on indicator X3 at T2bf05_17_t2 ~~ res4*bf05_17_t2 # This allows residual variance on indicator X4 at T2bf05_22_t2 ~~ res5*bf05_22_t2 # This allows residual variance on indicator X5 at T2bf05_27_t2 ~~ res6*bf05_27_t2 # This allows residual variance on indicator X6 at T2 bf05_32_t2 ~~ res7*bf05_32_t2 # This allows residual variance on indicator X7 at T2 bf05_37_t2 ~~ res8*bf05_37_t2 # This allows residual variance on indicator X8 at T2bf05_42_t2 ~~ res9*bf05_42_t2 # This allows residual variance on indicator X9 at T2bf05_47_t2 ~~ res10*bf05_47_t2 # This allows residual variance on indicator X10 at T2bf05_52_t2 ~~ res11*bf05_52_t2 # This allows residual variance on indicator X11 at T2bf05_57_t2 ~~ res12*bf05_57_t2 # This allows residual variance on indicator X12 at T2bf05_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_agree_curr_hyp5 <-lavaan(mi_lcs_agree_curr_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_curr_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with agreeableness change score (current-self) is not significantly different from zero, r = 0.021, p = 0.438.
3.7.1.6 Agreeableness - ideal-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_ideal_hyp5 <-'agree_t1 =~ 1*bf06_02_t1 + lamb2*bf06_07_t1 + lamb3*bf06_12_t1 + lamb4*bf06_17_t1 + lamb5*bf06_22_t1 + lamb6*bf06_27_t1 + lamb7*bf06_32_t1 + lamb8*bf06_37_t1 + lamb9*bf06_42_t1 + lamb10*bf06_47_t1 + lamb11*bf06_52_t1 + lamb12*bf06_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf06_02_t2 + lamb2*bf06_07_t2 + lamb3*bf06_12_t2 + lamb4*bf06_17_t2 + lamb5*bf06_22_t2 + lamb6*bf06_27_t2 + lamb7*bf06_32_t2 + lamb8*bf06_37_t2 + lamb9*bf06_42_t2 + lamb10*bf06_47_t2 + lamb11*bf06_52_t2 + lamb12*bf06_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsagree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf06_02_t1 ~~ bf06_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_07_t1 ~~ bf06_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_12_t1 ~~ bf06_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_17_t1 ~~ bf06_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_22_t1 ~~ bf06_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_27_t1 ~~ bf06_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_32_t1 ~~ bf06_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_37_t1 ~~ bf06_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_42_t1 ~~ bf06_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_47_t1 ~~ bf06_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_52_t1 ~~ bf06_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_57_t1 ~~ bf06_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_02_t1 ~~ res1*bf06_02_t1 # This allows residual variance on indicator X1 at T1 bf06_07_t1 ~~ res2*bf06_07_t1 # This allows residual variance on indicator X2 at T1bf06_12_t1 ~~ res3*bf06_12_t1 # This allows residual variance on indicator X3 at T1bf06_17_t1 ~~ res4*bf06_17_t1 # This allows residual variance on indicator X4 at T1bf06_22_t1 ~~ res5*bf06_22_t1 # This allows residual variance on indicator X5 at T1bf06_27_t1 ~~ res6*bf06_27_t1 # This allows residual variance on indicator X6 at T1 bf06_32_t1 ~~ res7*bf06_32_t1 # This allows residual variance on indicator X7 at T1bf06_37_t1 ~~ res8*bf06_37_t1 # This allows residual variance on indicator X8 at T1bf06_42_t1 ~~ res9*bf06_42_t1 # This allows residual variance on indicator X9 at T1bf06_47_t1 ~~ res10*bf06_47_t1 # This allows residual variance on indicator X10 at T1bf06_52_t1 ~~ res11*bf06_52_t1 # This allows residual variance on indicator X11 at T1bf06_57_t1 ~~ res12*bf06_57_t1 # This allows residual variance on indicator X12 at T1bf06_02_t2 ~~ res1*bf06_02_t2 # This allows residual variance on indicator X1 at T2 bf06_07_t2 ~~ res2*bf06_07_t2 # This allows residual variance on indicator X2 at T2 bf06_12_t2 ~~ res3*bf06_12_t2 # This allows residual variance on indicator X3 at T2bf06_17_t2 ~~ res4*bf06_17_t2 # This allows residual variance on indicator X4 at T2bf06_22_t2 ~~ res5*bf06_22_t2 # This allows residual variance on indicator X5 at T2bf06_27_t2 ~~ res6*bf06_27_t2 # This allows residual variance on indicator X6 at T2 bf06_32_t2 ~~ res7*bf06_32_t2 # This allows residual variance on indicator X7 at T2 bf06_37_t2 ~~ res8*bf06_37_t2 # This allows residual variance on indicator X8 at T2bf06_42_t2 ~~ res9*bf06_42_t2 # This allows residual variance on indicator X9 at T2bf06_47_t2 ~~ res10*bf06_47_t2 # This allows residual variance on indicator X10 at T2bf06_52_t2 ~~ res11*bf06_52_t2 # This allows residual variance on indicator X11 at T2bf06_57_t2 ~~ res12*bf06_57_t2 # This allows residual variance on indicator X12 at T2bf06_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_agree_ideal_hyp5 <-lavaan(mi_lcs_agree_ideal_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_ideal_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_curr_specif_hyp5 <-'agree_t1 =~ 1*bf05_02_t1 + lamb2*bf05_07_t1 + lamb3*bf05_12_t1 + lamb4*bf05_17_t1 + lamb5*bf05_22_t1 + lamb6*bf05_27_t1 + lamb7*bf05_32_t1 + lamb8*bf05_37_t1 + lamb9*bf05_42_t1 + lamb10*bf05_47_t1 + lamb11*bf05_52_t1 + lamb12*bf05_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf05_02_t2 + lamb2*bf05_07_t2 + lamb3*bf05_12_t2 + lamb4*bf05_17_t2 + lamb5*bf05_22_t2 + lamb6*bf05_27_t2 + lamb7*bf05_32_t2 + lamb8*bf05_37_t2 + lamb9*bf05_42_t2 + lamb10*bf05_47_t2 + lamb11*bf05_52_t2 + lamb12*bf05_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_04_t1 + sa07_05_t1 + sa07_06_t1 # latent acceptance goal variable (three facets per trait)agree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf05_02_t1 ~~ bf05_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_07_t1 ~~ bf05_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_12_t1 ~~ bf05_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_17_t1 ~~ bf05_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_22_t1 ~~ bf05_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_27_t1 ~~ bf05_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_32_t1 ~~ bf05_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_37_t1 ~~ bf05_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_42_t1 ~~ bf05_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_47_t1 ~~ bf05_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_52_t1 ~~ bf05_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_57_t1 ~~ bf05_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_02_t1 ~~ res1*bf05_02_t1 # This allows residual variance on indicator X1 at T1 bf05_07_t1 ~~ res2*bf05_07_t1 # This allows residual variance on indicator X2 at T1bf05_12_t1 ~~ res3*bf05_12_t1 # This allows residual variance on indicator X3 at T1bf05_17_t1 ~~ res4*bf05_17_t1 # This allows residual variance on indicator X4 at T1bf05_22_t1 ~~ res5*bf05_22_t1 # This allows residual variance on indicator X5 at T1bf05_27_t1 ~~ res6*bf05_27_t1 # This allows residual variance on indicator X6 at T1 bf05_32_t1 ~~ res7*bf05_32_t1 # This allows residual variance on indicator X7 at T1bf05_37_t1 ~~ res8*bf05_37_t1 # This allows residual variance on indicator X8 at T1bf05_42_t1 ~~ res9*bf05_42_t1 # This allows residual variance on indicator X9 at T1bf05_47_t1 ~~ res10*bf05_47_t1 # This allows residual variance on indicator X10 at T1bf05_52_t1 ~~ res11*bf05_52_t1 # This allows residual variance on indicator X11 at T1bf05_57_t1 ~~ res12*bf05_57_t1 # This allows residual variance on indicator X12 at T1bf05_02_t2 ~~ res1*bf05_02_t2 # This allows residual variance on indicator X1 at T2 bf05_07_t2 ~~ res2*bf05_07_t2 # This allows residual variance on indicator X2 at T2 bf05_12_t2 ~~ res3*bf05_12_t2 # This allows residual variance on indicator X3 at T2bf05_17_t2 ~~ res4*bf05_17_t2 # This allows residual variance on indicator X4 at T2bf05_22_t2 ~~ res5*bf05_22_t2 # This allows residual variance on indicator X5 at T2bf05_27_t2 ~~ res6*bf05_27_t2 # This allows residual variance on indicator X6 at T2 bf05_32_t2 ~~ res7*bf05_32_t2 # This allows residual variance on indicator X7 at T2 bf05_37_t2 ~~ res8*bf05_37_t2 # This allows residual variance on indicator X8 at T2bf05_42_t2 ~~ res9*bf05_42_t2 # This allows residual variance on indicator X9 at T2bf05_47_t2 ~~ res10*bf05_47_t2 # This allows residual variance on indicator X10 at T2bf05_52_t2 ~~ res11*bf05_52_t2 # This allows residual variance on indicator X11 at T2bf05_57_t2 ~~ res12*bf05_57_t2 # This allows residual variance on indicator X12 at T2bf05_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_04_t1 ~~ sa07_04_t1sa07_05_t1 ~~ sa07_05_t1sa07_06_t1 ~~ sa07_06_t1sa07_04_t1 ~ 1sa07_05_t1 ~ 1sa07_06_t1 ~ 1'fit_mi_lcs_agree_curr_specif_hyp5 <-lavaan(mi_lcs_agree_curr_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_curr_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with agreeableness change score (current-self) is not significantly different from zero, r = 0.011, p = 0.605.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_agree_ideal_specif_hyp5 <-'agree_t1 =~ 1*bf06_02_t1 + lamb2*bf06_07_t1 + lamb3*bf06_12_t1 + lamb4*bf06_17_t1 + lamb5*bf06_22_t1 + lamb6*bf06_27_t1 + lamb7*bf06_32_t1 + lamb8*bf06_37_t1 + lamb9*bf06_42_t1 + lamb10*bf06_47_t1 + lamb11*bf06_52_t1 + lamb12*bf06_57_t1 # This specifies the measurement model for agree_t1 agree_t2 =~ 1*bf06_02_t2 + lamb2*bf06_07_t2 + lamb3*bf06_12_t2 + lamb4*bf06_17_t2 + lamb5*bf06_22_t2 + lamb6*bf06_27_t2 + lamb7*bf06_32_t2 + lamb8*bf06_37_t2 + lamb9*bf06_42_t2 + lamb10*bf06_47_t2 + lamb11*bf06_52_t2 + lamb12*bf06_57_t2 # This specifies the measurement model for agree_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_04_t1 + sa07_05_t1 + sa07_06_t1 # latent acceptance goal variable (three facets per trait)agree_t2 ~ 1*agree_t1 # This parameter regresses agree_t2 perfectly on agree_t1d_agree_1 =~ 1*agree_t2 # This defines the latent change score factor as measured perfectly by scores on agree_t2agree_t2 ~ 0*1 # This line constrains the intercept of agree_t2 to 0agree_t2 ~~ 0*agree_t2 # This fixes the variance of agree_t2 to 0d_agree_1 ~ 1 # This estimates the intercept of the change score agree_t1 ~ 1 # This estimates the intercept of agree_t1 d_agree_1 ~~ d_agree_1 # This estimates the variance of the change scores agree_t1 ~~ agree_t1 # This estimates the variance of the agree_t1 d_agree_1 ~ agree_t1 # This estimates the self-feedback parameterd_agree_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf06_02_t1 ~~ bf06_02_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_07_t1 ~~ bf06_07_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_12_t1 ~~ bf06_12_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_17_t1 ~~ bf06_17_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_22_t1 ~~ bf06_22_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_27_t1 ~~ bf06_27_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_32_t1 ~~ bf06_32_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_37_t1 ~~ bf06_37_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_42_t1 ~~ bf06_42_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_47_t1 ~~ bf06_47_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_52_t1 ~~ bf06_52_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_57_t1 ~~ bf06_57_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_02_t1 ~~ res1*bf06_02_t1 # This allows residual variance on indicator X1 at T1 bf06_07_t1 ~~ res2*bf06_07_t1 # This allows residual variance on indicator X2 at T1bf06_12_t1 ~~ res3*bf06_12_t1 # This allows residual variance on indicator X3 at T1bf06_17_t1 ~~ res4*bf06_17_t1 # This allows residual variance on indicator X4 at T1bf06_22_t1 ~~ res5*bf06_22_t1 # This allows residual variance on indicator X5 at T1bf06_27_t1 ~~ res6*bf06_27_t1 # This allows residual variance on indicator X6 at T1 bf06_32_t1 ~~ res7*bf06_32_t1 # This allows residual variance on indicator X7 at T1bf06_37_t1 ~~ res8*bf06_37_t1 # This allows residual variance on indicator X8 at T1bf06_42_t1 ~~ res9*bf06_42_t1 # This allows residual variance on indicator X9 at T1bf06_47_t1 ~~ res10*bf06_47_t1 # This allows residual variance on indicator X10 at T1bf06_52_t1 ~~ res11*bf06_52_t1 # This allows residual variance on indicator X11 at T1bf06_57_t1 ~~ res12*bf06_57_t1 # This allows residual variance on indicator X12 at T1bf06_02_t2 ~~ res1*bf06_02_t2 # This allows residual variance on indicator X1 at T2 bf06_07_t2 ~~ res2*bf06_07_t2 # This allows residual variance on indicator X2 at T2 bf06_12_t2 ~~ res3*bf06_12_t2 # This allows residual variance on indicator X3 at T2bf06_17_t2 ~~ res4*bf06_17_t2 # This allows residual variance on indicator X4 at T2bf06_22_t2 ~~ res5*bf06_22_t2 # This allows residual variance on indicator X5 at T2bf06_27_t2 ~~ res6*bf06_27_t2 # This allows residual variance on indicator X6 at T2 bf06_32_t2 ~~ res7*bf06_32_t2 # This allows residual variance on indicator X7 at T2 bf06_37_t2 ~~ res8*bf06_37_t2 # This allows residual variance on indicator X8 at T2bf06_42_t2 ~~ res9*bf06_42_t2 # This allows residual variance on indicator X9 at T2bf06_47_t2 ~~ res10*bf06_47_t2 # This allows residual variance on indicator X10 at T2bf06_52_t2 ~~ res11*bf06_52_t2 # This allows residual variance on indicator X11 at T2bf06_57_t2 ~~ res12*bf06_57_t2 # This allows residual variance on indicator X12 at T2bf06_02_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_07_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_12_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_17_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_22_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_27_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_32_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_37_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_42_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_47_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_52_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_57_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_02_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_07_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_12_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_17_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_22_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_27_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_32_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_37_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_42_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_47_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_52_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_57_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_04_t1 ~~ sa07_04_t1sa07_05_t1 ~~ sa07_05_t1sa07_06_t1 ~~ sa07_06_t1sa07_04_t1 ~ 1sa07_05_t1 ~ 1sa07_06_t1 ~ 1'fit_mi_lcs_agree_ideal_specif_hyp5 <-lavaan(mi_lcs_agree_ideal_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_agree_ideal_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with agreeableness change score (ideal-self) is not significantly different from zero, r = -0.009, p = 0.74.
3.7.1.9 Conscientiousness - current-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_curr_hyp5 <-'consc_t1 =~ 1*bf05_03_t1 + lamb2*bf05_08_t1 + lamb3*bf05_13_t1 + lamb4*bf05_18_t1 + lamb5*bf05_23_t1 + lamb6*bf05_28_t1 + lamb7*bf05_33_t1 + lamb8*bf05_38_t1 + lamb9*bf05_43_t1 + lamb10*bf05_48_t1 + lamb11*bf05_53_t1 + lamb12*bf05_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf05_03_t2 + lamb2*bf05_08_t2 + lamb3*bf05_13_t2 + lamb4*bf05_18_t2 + lamb5*bf05_23_t2 + lamb6*bf05_28_t2 + lamb7*bf05_33_t2 + lamb8*bf05_38_t2 + lamb9*bf05_43_t2 + lamb10*bf05_48_t2 + lamb11*bf05_53_t2 + lamb12*bf05_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsconsc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf05_03_t1 ~~ bf05_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_08_t1 ~~ bf05_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_13_t1 ~~ bf05_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_18_t1 ~~ bf05_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_23_t1 ~~ bf05_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_28_t1 ~~ bf05_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_33_t1 ~~ bf05_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_38_t1 ~~ bf05_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_43_t1 ~~ bf05_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_48_t1 ~~ bf05_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_53_t1 ~~ bf05_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_58_t1 ~~ bf05_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_03_t1 ~~ res1*bf05_03_t1 # This allows residual variance on indicator X1 at T1 bf05_08_t1 ~~ res2*bf05_08_t1 # This allows residual variance on indicator X2 at T1bf05_13_t1 ~~ res3*bf05_13_t1 # This allows residual variance on indicator X3 at T1bf05_18_t1 ~~ res4*bf05_18_t1 # This allows residual variance on indicator X4 at T1bf05_23_t1 ~~ res5*bf05_23_t1 # This allows residual variance on indicator X5 at T1bf05_28_t1 ~~ res6*bf05_28_t1 # This allows residual variance on indicator X6 at T1 bf05_33_t1 ~~ res7*bf05_33_t1 # This allows residual variance on indicator X7 at T1bf05_38_t1 ~~ res8*bf05_38_t1 # This allows residual variance on indicator X8 at T1bf05_43_t1 ~~ res9*bf05_43_t1 # This allows residual variance on indicator X9 at T1bf05_48_t1 ~~ res10*bf05_48_t1 # This allows residual variance on indicator X10 at T1bf05_53_t1 ~~ res11*bf05_53_t1 # This allows residual variance on indicator X11 at T1bf05_58_t1 ~~ res12*bf05_58_t1 # This allows residual variance on indicator X12 at T1bf05_03_t2 ~~ res1*bf05_03_t2 # This allows residual variance on indicator X1 at T2 bf05_08_t2 ~~ res2*bf05_08_t2 # This allows residual variance on indicator X2 at T2 bf05_13_t2 ~~ res3*bf05_13_t2 # This allows residual variance on indicator X3 at T2bf05_18_t2 ~~ res4*bf05_18_t2 # This allows residual variance on indicator X4 at T2bf05_23_t2 ~~ res5*bf05_23_t2 # This allows residual variance on indicator X5 at T2bf05_28_t2 ~~ res6*bf05_28_t2 # This allows residual variance on indicator X6 at T2 bf05_33_t2 ~~ res7*bf05_33_t2 # This allows residual variance on indicator X7 at T2 bf05_38_t2 ~~ res8*bf05_38_t2 # This allows residual variance on indicator X8 at T2bf05_43_t2 ~~ res9*bf05_43_t2 # This allows residual variance on indicator X9 at T2bf05_48_t2 ~~ res10*bf05_48_t2 # This allows residual variance on indicator X10 at T2bf05_53_t2 ~~ res11*bf05_53_t2 # This allows residual variance on indicator X11 at T2bf05_58_t2 ~~ res12*bf05_58_t2 # This allows residual variance on indicator X12 at T2bf05_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_consc_curr_hyp5 <-lavaan(mi_lcs_consc_curr_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_curr_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with conscientiousness change score (current-self) is not significantly different from zero, r = 0.004, p = 0.891.
3.7.1.10 Conscientiousness - ideal-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_ideal_hyp5 <-'consc_t1 =~ 1*bf06_03_t1 + lamb2*bf06_08_t1 + lamb3*bf06_13_t1 + lamb4*bf06_18_t1 + lamb5*bf06_23_t1 + lamb6*bf06_28_t1 + lamb7*bf06_33_t1 + lamb8*bf06_38_t1 + lamb9*bf06_43_t1 + lamb10*bf06_48_t1 + lamb11*bf06_53_t1 + lamb12*bf06_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf06_03_t2 + lamb2*bf06_08_t2 + lamb3*bf06_13_t2 + lamb4*bf06_18_t2 + lamb5*bf06_23_t2 + lamb6*bf06_28_t2 + lamb7*bf06_33_t2 + lamb8*bf06_38_t2 + lamb9*bf06_43_t2 + lamb10*bf06_48_t2 + lamb11*bf06_53_t2 + lamb12*bf06_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsconsc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf06_03_t1 ~~ bf06_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_08_t1 ~~ bf06_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_13_t1 ~~ bf06_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_18_t1 ~~ bf06_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_23_t1 ~~ bf06_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_28_t1 ~~ bf06_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_33_t1 ~~ bf06_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_38_t1 ~~ bf06_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_43_t1 ~~ bf06_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_48_t1 ~~ bf06_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_53_t1 ~~ bf06_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_58_t1 ~~ bf06_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_03_t1 ~~ res1*bf06_03_t1 # This allows residual variance on indicator X1 at T1 bf06_08_t1 ~~ res2*bf06_08_t1 # This allows residual variance on indicator X2 at T1bf06_13_t1 ~~ res3*bf06_13_t1 # This allows residual variance on indicator X3 at T1bf06_18_t1 ~~ res4*bf06_18_t1 # This allows residual variance on indicator X4 at T1bf06_23_t1 ~~ res5*bf06_23_t1 # This allows residual variance on indicator X5 at T1bf06_28_t1 ~~ res6*bf06_28_t1 # This allows residual variance on indicator X6 at T1 bf06_33_t1 ~~ res7*bf06_33_t1 # This allows residual variance on indicator X7 at T1bf06_38_t1 ~~ res8*bf06_38_t1 # This allows residual variance on indicator X8 at T1bf06_43_t1 ~~ res9*bf06_43_t1 # This allows residual variance on indicator X9 at T1bf06_48_t1 ~~ res10*bf06_48_t1 # This allows residual variance on indicator X10 at T1bf06_53_t1 ~~ res11*bf06_53_t1 # This allows residual variance on indicator X11 at T1bf06_58_t1 ~~ res12*bf06_58_t1 # This allows residual variance on indicator X12 at T1bf06_03_t2 ~~ res1*bf06_03_t2 # This allows residual variance on indicator X1 at T2 bf06_08_t2 ~~ res2*bf06_08_t2 # This allows residual variance on indicator X2 at T2 bf06_13_t2 ~~ res3*bf06_13_t2 # This allows residual variance on indicator X3 at T2bf06_18_t2 ~~ res4*bf06_18_t2 # This allows residual variance on indicator X4 at T2bf06_23_t2 ~~ res5*bf06_23_t2 # This allows residual variance on indicator X5 at T2bf06_28_t2 ~~ res6*bf06_28_t2 # This allows residual variance on indicator X6 at T2 bf06_33_t2 ~~ res7*bf06_33_t2 # This allows residual variance on indicator X7 at T2 bf06_38_t2 ~~ res8*bf06_38_t2 # This allows residual variance on indicator X8 at T2bf06_43_t2 ~~ res9*bf06_43_t2 # This allows residual variance on indicator X9 at T2bf06_48_t2 ~~ res10*bf06_48_t2 # This allows residual variance on indicator X10 at T2bf06_53_t2 ~~ res11*bf06_53_t2 # This allows residual variance on indicator X11 at T2bf06_58_t2 ~~ res12*bf06_58_t2 # This allows residual variance on indicator X12 at T2bf06_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_consc_ideal_hyp5 <-lavaan(mi_lcs_consc_ideal_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_ideal_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with conscientiousness change score (ideal-self) is not significantly different from zero, r = 0.002, p = 0.914.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_curr_specif_hyp5 <-'consc_t1 =~ 1*bf05_03_t1 + lamb2*bf05_08_t1 + lamb3*bf05_13_t1 + lamb4*bf05_18_t1 + lamb5*bf05_23_t1 + lamb6*bf05_28_t1 + lamb7*bf05_33_t1 + lamb8*bf05_38_t1 + lamb9*bf05_43_t1 + lamb10*bf05_48_t1 + lamb11*bf05_53_t1 + lamb12*bf05_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf05_03_t2 + lamb2*bf05_08_t2 + lamb3*bf05_13_t2 + lamb4*bf05_18_t2 + lamb5*bf05_23_t2 + lamb6*bf05_28_t2 + lamb7*bf05_33_t2 + lamb8*bf05_38_t2 + lamb9*bf05_43_t2 + lamb10*bf05_48_t2 + lamb11*bf05_53_t2 + lamb12*bf05_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_07_t1 + sa07_08_t1 + sa07_09_t1 # latent acceptance goal variable (three facets per trait)consc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf05_03_t1 ~~ bf05_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_08_t1 ~~ bf05_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_13_t1 ~~ bf05_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_18_t1 ~~ bf05_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_23_t1 ~~ bf05_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_28_t1 ~~ bf05_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_33_t1 ~~ bf05_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_38_t1 ~~ bf05_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_43_t1 ~~ bf05_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_48_t1 ~~ bf05_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_53_t1 ~~ bf05_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_58_t1 ~~ bf05_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_03_t1 ~~ res1*bf05_03_t1 # This allows residual variance on indicator X1 at T1 bf05_08_t1 ~~ res2*bf05_08_t1 # This allows residual variance on indicator X2 at T1bf05_13_t1 ~~ res3*bf05_13_t1 # This allows residual variance on indicator X3 at T1bf05_18_t1 ~~ res4*bf05_18_t1 # This allows residual variance on indicator X4 at T1bf05_23_t1 ~~ res5*bf05_23_t1 # This allows residual variance on indicator X5 at T1bf05_28_t1 ~~ res6*bf05_28_t1 # This allows residual variance on indicator X6 at T1 bf05_33_t1 ~~ res7*bf05_33_t1 # This allows residual variance on indicator X7 at T1bf05_38_t1 ~~ res8*bf05_38_t1 # This allows residual variance on indicator X8 at T1bf05_43_t1 ~~ res9*bf05_43_t1 # This allows residual variance on indicator X9 at T1bf05_48_t1 ~~ res10*bf05_48_t1 # This allows residual variance on indicator X10 at T1bf05_53_t1 ~~ res11*bf05_53_t1 # This allows residual variance on indicator X11 at T1bf05_58_t1 ~~ res12*bf05_58_t1 # This allows residual variance on indicator X12 at T1bf05_03_t2 ~~ res1*bf05_03_t2 # This allows residual variance on indicator X1 at T2 bf05_08_t2 ~~ res2*bf05_08_t2 # This allows residual variance on indicator X2 at T2 bf05_13_t2 ~~ res3*bf05_13_t2 # This allows residual variance on indicator X3 at T2bf05_18_t2 ~~ res4*bf05_18_t2 # This allows residual variance on indicator X4 at T2bf05_23_t2 ~~ res5*bf05_23_t2 # This allows residual variance on indicator X5 at T2bf05_28_t2 ~~ res6*bf05_28_t2 # This allows residual variance on indicator X6 at T2 bf05_33_t2 ~~ res7*bf05_33_t2 # This allows residual variance on indicator X7 at T2 bf05_38_t2 ~~ res8*bf05_38_t2 # This allows residual variance on indicator X8 at T2bf05_43_t2 ~~ res9*bf05_43_t2 # This allows residual variance on indicator X9 at T2bf05_48_t2 ~~ res10*bf05_48_t2 # This allows residual variance on indicator X10 at T2bf05_53_t2 ~~ res11*bf05_53_t2 # This allows residual variance on indicator X11 at T2bf05_58_t2 ~~ res12*bf05_58_t2 # This allows residual variance on indicator X12 at T2bf05_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_07_t1 ~~ sa07_07_t1sa07_08_t1 ~~ sa07_08_t1sa07_09_t1 ~~ sa07_09_t1sa07_07_t1 ~ 1sa07_08_t1 ~ 1sa07_09_t1 ~ 1'fit_mi_lcs_consc_curr_specif_hyp5 <-lavaan(mi_lcs_consc_curr_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_curr_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with conscientiousness change score (current-self) is not significantly different from zero, r = 0.141, p = 0.021.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_consc_ideal_specif_hyp5 <-'consc_t1 =~ 1*bf06_03_t1 + lamb2*bf06_08_t1 + lamb3*bf06_13_t1 + lamb4*bf06_18_t1 + lamb5*bf06_23_t1 + lamb6*bf06_28_t1 + lamb7*bf06_33_t1 + lamb8*bf06_38_t1 + lamb9*bf06_43_t1 + lamb10*bf06_48_t1 + lamb11*bf06_53_t1 + lamb12*bf06_58_t1 # This specifies the measurement model for consc_t1 consc_t2 =~ 1*bf06_03_t2 + lamb2*bf06_08_t2 + lamb3*bf06_13_t2 + lamb4*bf06_18_t2 + lamb5*bf06_23_t2 + lamb6*bf06_28_t2 + lamb7*bf06_33_t2 + lamb8*bf06_38_t2 + lamb9*bf06_43_t2 + lamb10*bf06_48_t2 + lamb11*bf06_53_t2 + lamb12*bf06_58_t2 # This specifies the measurement model for consc_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_07_t1 + sa07_08_t1 + sa07_09_t1 # latent acceptance goal variable (three facets per trait)consc_t2 ~ 1*consc_t1 # This parameter regresses consc_t2 perfectly on consc_t1d_consc_1 =~ 1*consc_t2 # This defines the latent change score factor as measured perfectly by scores on consc_t2consc_t2 ~ 0*1 # This line constrains the intercept of consc_t2 to 0consc_t2 ~~ 0*consc_t2 # This fixes the variance of consc_t2 to 0d_consc_1 ~ 1 # This estimates the intercept of the change score consc_t1 ~ 1 # This estimates the intercept of consc_t1 d_consc_1 ~~ d_consc_1 # This estimates the variance of the change scores consc_t1 ~~ consc_t1 # This estimates the variance of the consc_t1 d_consc_1 ~ consc_t1 # This estimates the self-feedback parameterd_consc_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf06_03_t1 ~~ bf06_03_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_08_t1 ~~ bf06_08_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_13_t1 ~~ bf06_13_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_18_t1 ~~ bf06_18_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_23_t1 ~~ bf06_23_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_28_t1 ~~ bf06_28_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_33_t1 ~~ bf06_33_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_38_t1 ~~ bf06_38_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_43_t1 ~~ bf06_43_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_48_t1 ~~ bf06_48_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_53_t1 ~~ bf06_53_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_58_t1 ~~ bf06_58_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_03_t1 ~~ res1*bf06_03_t1 # This allows residual variance on indicator X1 at T1 bf06_08_t1 ~~ res2*bf06_08_t1 # This allows residual variance on indicator X2 at T1bf06_13_t1 ~~ res3*bf06_13_t1 # This allows residual variance on indicator X3 at T1bf06_18_t1 ~~ res4*bf06_18_t1 # This allows residual variance on indicator X4 at T1bf06_23_t1 ~~ res5*bf06_23_t1 # This allows residual variance on indicator X5 at T1bf06_28_t1 ~~ res6*bf06_28_t1 # This allows residual variance on indicator X6 at T1 bf06_33_t1 ~~ res7*bf06_33_t1 # This allows residual variance on indicator X7 at T1bf06_38_t1 ~~ res8*bf06_38_t1 # This allows residual variance on indicator X8 at T1bf06_43_t1 ~~ res9*bf06_43_t1 # This allows residual variance on indicator X9 at T1bf06_48_t1 ~~ res10*bf06_48_t1 # This allows residual variance on indicator X10 at T1bf06_53_t1 ~~ res11*bf06_53_t1 # This allows residual variance on indicator X11 at T1bf06_58_t1 ~~ res12*bf06_58_t1 # This allows residual variance on indicator X12 at T1bf06_03_t2 ~~ res1*bf06_03_t2 # This allows residual variance on indicator X1 at T2 bf06_08_t2 ~~ res2*bf06_08_t2 # This allows residual variance on indicator X2 at T2 bf06_13_t2 ~~ res3*bf06_13_t2 # This allows residual variance on indicator X3 at T2bf06_18_t2 ~~ res4*bf06_18_t2 # This allows residual variance on indicator X4 at T2bf06_23_t2 ~~ res5*bf06_23_t2 # This allows residual variance on indicator X5 at T2bf06_28_t2 ~~ res6*bf06_28_t2 # This allows residual variance on indicator X6 at T2 bf06_33_t2 ~~ res7*bf06_33_t2 # This allows residual variance on indicator X7 at T2 bf06_38_t2 ~~ res8*bf06_38_t2 # This allows residual variance on indicator X8 at T2bf06_43_t2 ~~ res9*bf06_43_t2 # This allows residual variance on indicator X9 at T2bf06_48_t2 ~~ res10*bf06_48_t2 # This allows residual variance on indicator X10 at T2bf06_53_t2 ~~ res11*bf06_53_t2 # This allows residual variance on indicator X11 at T2bf06_58_t2 ~~ res12*bf06_58_t2 # This allows residual variance on indicator X12 at T2bf06_03_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_08_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_13_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_18_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_23_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_28_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_33_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_38_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_43_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_48_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_53_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_58_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_03_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_08_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_13_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_18_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_23_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_28_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_33_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_38_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_43_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_48_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_53_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_58_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_07_t1 ~~ sa07_07_t1sa07_08_t1 ~~ sa07_08_t1sa07_09_t1 ~~ sa07_09_t1sa07_07_t1 ~ 1sa07_08_t1 ~ 1sa07_09_t1 ~ 1'fit_mi_lcs_consc_ideal_specif_hyp5 <-lavaan(mi_lcs_consc_ideal_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_consc_ideal_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
The correlation of specific, facet-level acceptance goals with the conscientiousness change score (ideal-self) is significantly different from zero, r = 0.034, p = 0.155.
3.7.1.13 Neuroticism - current-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_curr_hyp5 <-'neuro_t1 =~ 1*bf05_04_t1 + lamb2*bf05_09_t1 + lamb3*bf05_14_t1 + lamb4*bf05_19_t1 + lamb5*bf05_24_t1 + lamb6*bf05_29_t1 + lamb7*bf05_34_t1 + lamb8*bf05_39_t1 + lamb9*bf05_44_t1 + lamb10*bf05_49_t1 + lamb11*bf05_54_t1 + lamb12*bf05_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf05_04_t2 + lamb2*bf05_09_t2 + lamb3*bf05_14_t2 + lamb4*bf05_19_t2 + lamb5*bf05_24_t2 + lamb6*bf05_29_t2 + lamb7*bf05_34_t2 + lamb8*bf05_39_t2 + lamb9*bf05_44_t2 + lamb10*bf05_49_t2 + lamb11*bf05_54_t2 + lamb12*bf05_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsneuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf05_04_t1 ~~ bf05_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_09_t1 ~~ bf05_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_14_t1 ~~ bf05_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_19_t1 ~~ bf05_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_24_t1 ~~ bf05_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_29_t1 ~~ bf05_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_34_t1 ~~ bf05_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_39_t1 ~~ bf05_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_44_t1 ~~ bf05_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_49_t1 ~~ bf05_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_54_t1 ~~ bf05_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_59_t1 ~~ bf05_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_04_t1 ~~ res1*bf05_04_t1 # This allows residual variance on indicator X1 at T1 bf05_09_t1 ~~ res2*bf05_09_t1 # This allows residual variance on indicator X2 at T1bf05_14_t1 ~~ res3*bf05_14_t1 # This allows residual variance on indicator X3 at T1bf05_19_t1 ~~ res4*bf05_19_t1 # This allows residual variance on indicator X4 at T1bf05_24_t1 ~~ res5*bf05_24_t1 # This allows residual variance on indicator X5 at T1bf05_29_t1 ~~ res6*bf05_29_t1 # This allows residual variance on indicator X6 at T1 bf05_34_t1 ~~ res7*bf05_34_t1 # This allows residual variance on indicator X7 at T1bf05_39_t1 ~~ res8*bf05_39_t1 # This allows residual variance on indicator X8 at T1bf05_44_t1 ~~ res9*bf05_44_t1 # This allows residual variance on indicator X9 at T1bf05_49_t1 ~~ res10*bf05_49_t1 # This allows residual variance on indicator X10 at T1bf05_54_t1 ~~ res11*bf05_54_t1 # This allows residual variance on indicator X11 at T1bf05_59_t1 ~~ res12*bf05_59_t1 # This allows residual variance on indicator X12 at T1bf05_04_t2 ~~ res1*bf05_04_t2 # This allows residual variance on indicator X1 at T2 bf05_09_t2 ~~ res2*bf05_09_t2 # This allows residual variance on indicator X2 at T2 bf05_14_t2 ~~ res3*bf05_14_t2 # This allows residual variance on indicator X3 at T2bf05_19_t2 ~~ res4*bf05_19_t2 # This allows residual variance on indicator X4 at T2bf05_24_t2 ~~ res5*bf05_24_t2 # This allows residual variance on indicator X5 at T2bf05_29_t2 ~~ res6*bf05_29_t2 # This allows residual variance on indicator X6 at T2 bf05_34_t2 ~~ res7*bf05_34_t2 # This allows residual variance on indicator X7 at T2 bf05_39_t2 ~~ res8*bf05_39_t2 # This allows residual variance on indicator X8 at T2bf05_44_t2 ~~ res9*bf05_44_t2 # This allows residual variance on indicator X9 at T2bf05_49_t2 ~~ res10*bf05_49_t2 # This allows residual variance on indicator X10 at T2bf05_54_t2 ~~ res11*bf05_54_t2 # This allows residual variance on indicator X11 at T2bf05_59_t2 ~~ res12*bf05_59_t2 # This allows residual variance on indicator X12 at T2bf05_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_neuro_curr_hyp5 <-lavaan(mi_lcs_neuro_curr_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_curr_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with neuroticism change score (current-self) is not significantly different from zero, r = 0.056, p = 0.1.
3.7.1.14 Neuroticism - ideal-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_ideal_hyp5 <-'neuro_t1 =~ 1*bf06_04_t1 + lamb2*bf06_09_t1 + lamb3*bf06_14_t1 + lamb4*bf06_19_t1 + lamb5*bf06_24_t1 + lamb6*bf06_29_t1 + lamb7*bf06_34_t1 + lamb8*bf06_39_t1 + lamb9*bf06_44_t1 + lamb10*bf06_49_t1 + lamb11*bf06_54_t1 + lamb12*bf06_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf06_04_t2 + lamb2*bf06_09_t2 + lamb3*bf06_14_t2 + lamb4*bf06_19_t2 + lamb5*bf06_24_t2 + lamb6*bf06_29_t2 + lamb7*bf06_34_t2 + lamb8*bf06_39_t2 + lamb9*bf06_44_t2 + lamb10*bf06_49_t2 + lamb11*bf06_54_t2 + lamb12*bf06_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsneuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf06_04_t1 ~~ bf06_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_09_t1 ~~ bf06_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_14_t1 ~~ bf06_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_19_t1 ~~ bf06_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_24_t1 ~~ bf06_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_29_t1 ~~ bf06_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_34_t1 ~~ bf06_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_39_t1 ~~ bf06_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_44_t1 ~~ bf06_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_49_t1 ~~ bf06_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_54_t1 ~~ bf06_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_59_t1 ~~ bf06_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_04_t1 ~~ res1*bf06_04_t1 # This allows residual variance on indicator X1 at T1 bf06_09_t1 ~~ res2*bf06_09_t1 # This allows residual variance on indicator X2 at T1bf06_14_t1 ~~ res3*bf06_14_t1 # This allows residual variance on indicator X3 at T1bf06_19_t1 ~~ res4*bf06_19_t1 # This allows residual variance on indicator X4 at T1bf06_24_t1 ~~ res5*bf06_24_t1 # This allows residual variance on indicator X5 at T1bf06_29_t1 ~~ res6*bf06_29_t1 # This allows residual variance on indicator X6 at T1 bf06_34_t1 ~~ res7*bf06_34_t1 # This allows residual variance on indicator X7 at T1bf06_39_t1 ~~ res8*bf06_39_t1 # This allows residual variance on indicator X8 at T1bf06_44_t1 ~~ res9*bf06_44_t1 # This allows residual variance on indicator X9 at T1bf06_49_t1 ~~ res10*bf06_49_t1 # This allows residual variance on indicator X10 at T1bf06_54_t1 ~~ res11*bf06_54_t1 # This allows residual variance on indicator X11 at T1bf06_59_t1 ~~ res12*bf06_59_t1 # This allows residual variance on indicator X12 at T1bf06_04_t2 ~~ res1*bf06_04_t2 # This allows residual variance on indicator X1 at T2 bf06_09_t2 ~~ res2*bf06_09_t2 # This allows residual variance on indicator X2 at T2 bf06_14_t2 ~~ res3*bf06_14_t2 # This allows residual variance on indicator X3 at T2bf06_19_t2 ~~ res4*bf06_19_t2 # This allows residual variance on indicator X4 at T2bf06_24_t2 ~~ res5*bf06_24_t2 # This allows residual variance on indicator X5 at T2bf06_29_t2 ~~ res6*bf06_29_t2 # This allows residual variance on indicator X6 at T2 bf06_34_t2 ~~ res7*bf06_34_t2 # This allows residual variance on indicator X7 at T2 bf06_39_t2 ~~ res8*bf06_39_t2 # This allows residual variance on indicator X8 at T2bf06_44_t2 ~~ res9*bf06_44_t2 # This allows residual variance on indicator X9 at T2bf06_49_t2 ~~ res10*bf06_49_t2 # This allows residual variance on indicator X10 at T2bf06_54_t2 ~~ res11*bf06_54_t2 # This allows residual variance on indicator X11 at T2bf06_59_t2 ~~ res12*bf06_59_t2 # This allows residual variance on indicator X12 at T2bf06_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_neuro_ideal_hyp5 <-lavaan(mi_lcs_neuro_ideal_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_ideal_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_curr_specif_hyp5 <-'neuro_t1 =~ 1*bf05_04_t1 + lamb2*bf05_09_t1 + lamb3*bf05_14_t1 + lamb4*bf05_19_t1 + lamb5*bf05_24_t1 + lamb6*bf05_29_t1 + lamb7*bf05_34_t1 + lamb8*bf05_39_t1 + lamb9*bf05_44_t1 + lamb10*bf05_49_t1 + lamb11*bf05_54_t1 + lamb12*bf05_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf05_04_t2 + lamb2*bf05_09_t2 + lamb3*bf05_14_t2 + lamb4*bf05_19_t2 + lamb5*bf05_24_t2 + lamb6*bf05_29_t2 + lamb7*bf05_34_t2 + lamb8*bf05_39_t2 + lamb9*bf05_44_t2 + lamb10*bf05_49_t2 + lamb11*bf05_54_t2 + lamb12*bf05_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_10_t1 + sa07_11_t1 + sa07_12_t1 # latent acceptance goal variable (three facets per trait)neuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf05_04_t1 ~~ bf05_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_09_t1 ~~ bf05_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_14_t1 ~~ bf05_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_19_t1 ~~ bf05_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_24_t1 ~~ bf05_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_29_t1 ~~ bf05_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_34_t1 ~~ bf05_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_39_t1 ~~ bf05_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_44_t1 ~~ bf05_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_49_t1 ~~ bf05_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_54_t1 ~~ bf05_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_59_t1 ~~ bf05_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_04_t1 ~~ res1*bf05_04_t1 # This allows residual variance on indicator X1 at T1 bf05_09_t1 ~~ res2*bf05_09_t1 # This allows residual variance on indicator X2 at T1bf05_14_t1 ~~ res3*bf05_14_t1 # This allows residual variance on indicator X3 at T1bf05_19_t1 ~~ res4*bf05_19_t1 # This allows residual variance on indicator X4 at T1bf05_24_t1 ~~ res5*bf05_24_t1 # This allows residual variance on indicator X5 at T1bf05_29_t1 ~~ res6*bf05_29_t1 # This allows residual variance on indicator X6 at T1 bf05_34_t1 ~~ res7*bf05_34_t1 # This allows residual variance on indicator X7 at T1bf05_39_t1 ~~ res8*bf05_39_t1 # This allows residual variance on indicator X8 at T1bf05_44_t1 ~~ res9*bf05_44_t1 # This allows residual variance on indicator X9 at T1bf05_49_t1 ~~ res10*bf05_49_t1 # This allows residual variance on indicator X10 at T1bf05_54_t1 ~~ res11*bf05_54_t1 # This allows residual variance on indicator X11 at T1bf05_59_t1 ~~ res12*bf05_59_t1 # This allows residual variance on indicator X12 at T1bf05_04_t2 ~~ res1*bf05_04_t2 # This allows residual variance on indicator X1 at T2 bf05_09_t2 ~~ res2*bf05_09_t2 # This allows residual variance on indicator X2 at T2 bf05_14_t2 ~~ res3*bf05_14_t2 # This allows residual variance on indicator X3 at T2bf05_19_t2 ~~ res4*bf05_19_t2 # This allows residual variance on indicator X4 at T2bf05_24_t2 ~~ res5*bf05_24_t2 # This allows residual variance on indicator X5 at T2bf05_29_t2 ~~ res6*bf05_29_t2 # This allows residual variance on indicator X6 at T2 bf05_34_t2 ~~ res7*bf05_34_t2 # This allows residual variance on indicator X7 at T2 bf05_39_t2 ~~ res8*bf05_39_t2 # This allows residual variance on indicator X8 at T2bf05_44_t2 ~~ res9*bf05_44_t2 # This allows residual variance on indicator X9 at T2bf05_49_t2 ~~ res10*bf05_49_t2 # This allows residual variance on indicator X10 at T2bf05_54_t2 ~~ res11*bf05_54_t2 # This allows residual variance on indicator X11 at T2bf05_59_t2 ~~ res12*bf05_59_t2 # This allows residual variance on indicator X12 at T2bf05_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_10_t1 ~~ sa07_10_t1sa07_11_t1 ~~ sa07_11_t1sa07_12_t1 ~~ sa07_12_t1sa07_10_t1 ~ 1sa07_11_t1 ~ 1sa07_12_t1 ~ 1'fit_mi_lcs_neuro_curr_specif_hyp5 <-lavaan(mi_lcs_neuro_curr_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_curr_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with neuroticism change score (current-self) is significantly different from zero, r = -0.035, p = 0.371.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_neuro_ideal_specif_hyp5 <-'neuro_t1 =~ 1*bf06_04_t1 + lamb2*bf06_09_t1 + lamb3*bf06_14_t1 + lamb4*bf06_19_t1 + lamb5*bf06_24_t1 + lamb6*bf06_29_t1 + lamb7*bf06_34_t1 + lamb8*bf06_39_t1 + lamb9*bf06_44_t1 + lamb10*bf06_49_t1 + lamb11*bf06_54_t1 + lamb12*bf06_59_t1 # This specifies the measurement model for neuro_t1 neuro_t2 =~ 1*bf06_04_t2 + lamb2*bf06_09_t2 + lamb3*bf06_14_t2 + lamb4*bf06_19_t2 + lamb5*bf06_24_t2 + lamb6*bf06_29_t2 + lamb7*bf06_34_t2 + lamb8*bf06_39_t2 + lamb9*bf06_44_t2 + lamb10*bf06_49_t2 + lamb11*bf06_54_t2 + lamb12*bf06_59_t2 # This specifies the measurement model for neuro_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_10_t1 + sa07_11_t1 + sa07_12_t1 # latent acceptance goal variable (three facets per trait)neuro_t2 ~ 1*neuro_t1 # This parameter regresses neuro_t2 perfectly on neuro_t1d_neuro_1 =~ 1*neuro_t2 # This defines the latent change score factor as measured perfectly by scores on neuro_t2neuro_t2 ~ 0*1 # This line constrains the intercept of neuro_t2 to 0neuro_t2 ~~ 0*neuro_t2 # This fixes the variance of neuro_t2 to 0d_neuro_1 ~ 1 # This estimates the intercept of the change score neuro_t1 ~ 1 # This estimates the intercept of neuro_t1 d_neuro_1 ~~ d_neuro_1 # This estimates the variance of the change scores neuro_t1 ~~ neuro_t1 # This estimates the variance of the neuro_t1 d_neuro_1 ~ neuro_t1 # This estimates the self-feedback parameterd_neuro_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf06_04_t1 ~~ bf06_04_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_09_t1 ~~ bf06_09_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_14_t1 ~~ bf06_14_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_19_t1 ~~ bf06_19_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_24_t1 ~~ bf06_24_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_29_t1 ~~ bf06_29_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_34_t1 ~~ bf06_34_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_39_t1 ~~ bf06_39_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_44_t1 ~~ bf06_44_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_49_t1 ~~ bf06_49_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_54_t1 ~~ bf06_54_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_59_t1 ~~ bf06_59_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_04_t1 ~~ res1*bf06_04_t1 # This allows residual variance on indicator X1 at T1 bf06_09_t1 ~~ res2*bf06_09_t1 # This allows residual variance on indicator X2 at T1bf06_14_t1 ~~ res3*bf06_14_t1 # This allows residual variance on indicator X3 at T1bf06_19_t1 ~~ res4*bf06_19_t1 # This allows residual variance on indicator X4 at T1bf06_24_t1 ~~ res5*bf06_24_t1 # This allows residual variance on indicator X5 at T1bf06_29_t1 ~~ res6*bf06_29_t1 # This allows residual variance on indicator X6 at T1 bf06_34_t1 ~~ res7*bf06_34_t1 # This allows residual variance on indicator X7 at T1bf06_39_t1 ~~ res8*bf06_39_t1 # This allows residual variance on indicator X8 at T1bf06_44_t1 ~~ res9*bf06_44_t1 # This allows residual variance on indicator X9 at T1bf06_49_t1 ~~ res10*bf06_49_t1 # This allows residual variance on indicator X10 at T1bf06_54_t1 ~~ res11*bf06_54_t1 # This allows residual variance on indicator X11 at T1bf06_59_t1 ~~ res12*bf06_59_t1 # This allows residual variance on indicator X12 at T1bf06_04_t2 ~~ res1*bf06_04_t2 # This allows residual variance on indicator X1 at T2 bf06_09_t2 ~~ res2*bf06_09_t2 # This allows residual variance on indicator X2 at T2 bf06_14_t2 ~~ res3*bf06_14_t2 # This allows residual variance on indicator X3 at T2bf06_19_t2 ~~ res4*bf06_19_t2 # This allows residual variance on indicator X4 at T2bf06_24_t2 ~~ res5*bf06_24_t2 # This allows residual variance on indicator X5 at T2bf06_29_t2 ~~ res6*bf06_29_t2 # This allows residual variance on indicator X6 at T2 bf06_34_t2 ~~ res7*bf06_34_t2 # This allows residual variance on indicator X7 at T2 bf06_39_t2 ~~ res8*bf06_39_t2 # This allows residual variance on indicator X8 at T2bf06_44_t2 ~~ res9*bf06_44_t2 # This allows residual variance on indicator X9 at T2bf06_49_t2 ~~ res10*bf06_49_t2 # This allows residual variance on indicator X10 at T2bf06_54_t2 ~~ res11*bf06_54_t2 # This allows residual variance on indicator X11 at T2bf06_59_t2 ~~ res12*bf06_59_t2 # This allows residual variance on indicator X12 at T2bf06_04_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_09_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_14_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_19_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_24_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_29_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_34_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_39_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_44_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_49_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_54_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_59_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_04_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_09_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_14_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_19_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_24_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_29_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_34_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_39_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_44_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_49_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_54_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_59_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_10_t1 ~~ sa07_10_t1sa07_11_t1 ~~ sa07_11_t1sa07_12_t1 ~~ sa07_12_t1sa07_10_t1 ~ 1sa07_11_t1 ~ 1sa07_12_t1 ~ 1'fit_mi_lcs_neuro_ideal_specif_hyp5 <-lavaan(mi_lcs_neuro_ideal_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_neuro_ideal_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
The correlation of specific, facet-level acceptance goals with the neuroticism change score (ideal-self) is significantly different from zero, r = -0.041, p = 0.002.
3.7.1.17 Openness - current-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_curr_hyp5 <-'openn_t1 =~ 1*bf05_05_t1 + lamb2*bf05_10_t1 + lamb3*bf05_15_t1 + lamb4*bf05_20_t1 + lamb5*bf05_25_t1 + lamb6*bf05_30_t1 + lamb7*bf05_35_t1 + lamb8*bf05_40_t1 + lamb9*bf05_45_t1 + lamb10*bf05_50_t1 + lamb11*bf05_55_t1 + lamb12*bf05_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf05_05_t2 + lamb2*bf05_10_t2 + lamb3*bf05_15_t2 + lamb4*bf05_20_t2 + lamb5*bf05_25_t2 + lamb6*bf05_30_t2 + lamb7*bf05_35_t2 + lamb8*bf05_40_t2 + lamb9*bf05_45_t2 + lamb10*bf05_50_t2 + lamb11*bf05_55_t2 + lamb12*bf05_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsopenn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf05_05_t1 ~~ bf05_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_10_t1 ~~ bf05_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_15_t1 ~~ bf05_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_20_t1 ~~ bf05_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_25_t1 ~~ bf05_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_30_t1 ~~ bf05_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_35_t1 ~~ bf05_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_40_t1 ~~ bf05_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_45_t1 ~~ bf05_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_50_t1 ~~ bf05_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_55_t1 ~~ bf05_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_60_t1 ~~ bf05_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_05_t1 ~~ res1*bf05_05_t1 # This allows residual variance on indicator X1 at T1 bf05_10_t1 ~~ res2*bf05_10_t1 # This allows residual variance on indicator X2 at T1bf05_15_t1 ~~ res3*bf05_15_t1 # This allows residual variance on indicator X3 at T1bf05_20_t1 ~~ res4*bf05_20_t1 # This allows residual variance on indicator X4 at T1bf05_25_t1 ~~ res5*bf05_25_t1 # This allows residual variance on indicator X5 at T1bf05_30_t1 ~~ res6*bf05_30_t1 # This allows residual variance on indicator X6 at T1 bf05_35_t1 ~~ res7*bf05_35_t1 # This allows residual variance on indicator X7 at T1bf05_40_t1 ~~ res8*bf05_40_t1 # This allows residual variance on indicator X8 at T1bf05_45_t1 ~~ res9*bf05_45_t1 # This allows residual variance on indicator X9 at T1bf05_50_t1 ~~ res10*bf05_50_t1 # This allows residual variance on indicator X10 at T1bf05_55_t1 ~~ res11*bf05_55_t1 # This allows residual variance on indicator X11 at T1bf05_60_t1 ~~ res12*bf05_60_t1 # This allows residual variance on indicator X12 at T1bf05_05_t2 ~~ res1*bf05_05_t2 # This allows residual variance on indicator X1 at T2 bf05_10_t2 ~~ res2*bf05_10_t2 # This allows residual variance on indicator X2 at T2 bf05_15_t2 ~~ res3*bf05_15_t2 # This allows residual variance on indicator X3 at T2bf05_20_t2 ~~ res4*bf05_20_t2 # This allows residual variance on indicator X4 at T2bf05_25_t2 ~~ res5*bf05_25_t2 # This allows residual variance on indicator X5 at T2bf05_30_t2 ~~ res6*bf05_30_t2 # This allows residual variance on indicator X6 at T2 bf05_35_t2 ~~ res7*bf05_35_t2 # This allows residual variance on indicator X7 at T2 bf05_40_t2 ~~ res8*bf05_40_t2 # This allows residual variance on indicator X8 at T2bf05_45_t2 ~~ res9*bf05_45_t2 # This allows residual variance on indicator X9 at T2bf05_50_t2 ~~ res10*bf05_50_t2 # This allows residual variance on indicator X10 at T2bf05_55_t2 ~~ res11*bf05_55_t2 # This allows residual variance on indicator X11 at T2bf05_60_t2 ~~ res12*bf05_60_t2 # This allows residual variance on indicator X12 at T2bf05_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_openn_curr_hyp5 <-lavaan(mi_lcs_openn_curr_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_curr_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with openness change score (current-self) is not significantly different from zero, r = -0.003, p = 0.429.
3.7.1.18 Openness - ideal-self: general acceptance goals
Fit model:
Show the code
# adding correlation with manifest acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_ideal_hyp5 <-'openn_t1 =~ 1*bf06_05_t1 + lamb2*bf06_10_t1 + lamb3*bf06_15_t1 + lamb4*bf06_20_t1 + lamb5*bf06_25_t1 + lamb6*bf06_30_t1 + lamb7*bf06_35_t1 + lamb8*bf06_40_t1 + lamb9*bf06_45_t1 + lamb10*bf06_50_t1 + lamb11*bf06_55_t1 + lamb12*bf06_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf06_05_t2 + lamb2*bf06_10_t2 + lamb3*bf06_15_t2 + lamb4*bf06_20_t2 + lamb5*bf06_25_t2 + lamb6*bf06_30_t2 + lamb7*bf06_35_t2 + lamb8*bf06_40_t2 + lamb9*bf06_45_t2 + lamb10*bf06_50_t2 + lamb11*bf06_55_t2 + lamb12*bf06_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsopenn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ sa06_01_t1 # estimates the covariance/correlation with acceptance goal variablebf06_05_t1 ~~ bf06_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_10_t1 ~~ bf06_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_15_t1 ~~ bf06_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_20_t1 ~~ bf06_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_25_t1 ~~ bf06_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_30_t1 ~~ bf06_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_35_t1 ~~ bf06_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_40_t1 ~~ bf06_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_45_t1 ~~ bf06_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_50_t1 ~~ bf06_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_55_t1 ~~ bf06_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_60_t1 ~~ bf06_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_05_t1 ~~ res1*bf06_05_t1 # This allows residual variance on indicator X1 at T1 bf06_10_t1 ~~ res2*bf06_10_t1 # This allows residual variance on indicator X2 at T1bf06_15_t1 ~~ res3*bf06_15_t1 # This allows residual variance on indicator X3 at T1bf06_20_t1 ~~ res4*bf06_20_t1 # This allows residual variance on indicator X4 at T1bf06_25_t1 ~~ res5*bf06_25_t1 # This allows residual variance on indicator X5 at T1bf06_30_t1 ~~ res6*bf06_30_t1 # This allows residual variance on indicator X6 at T1 bf06_35_t1 ~~ res7*bf06_35_t1 # This allows residual variance on indicator X7 at T1bf06_40_t1 ~~ res8*bf06_40_t1 # This allows residual variance on indicator X8 at T1bf06_45_t1 ~~ res9*bf06_45_t1 # This allows residual variance on indicator X9 at T1bf06_50_t1 ~~ res10*bf06_50_t1 # This allows residual variance on indicator X10 at T1bf06_55_t1 ~~ res11*bf06_55_t1 # This allows residual variance on indicator X11 at T1bf06_60_t1 ~~ res12*bf06_60_t1 # This allows residual variance on indicator X12 at T1bf06_05_t2 ~~ res1*bf06_05_t2 # This allows residual variance on indicator X1 at T2 bf06_10_t2 ~~ res2*bf06_10_t2 # This allows residual variance on indicator X2 at T2 bf06_15_t2 ~~ res3*bf06_15_t2 # This allows residual variance on indicator X3 at T2bf06_20_t2 ~~ res4*bf06_20_t2 # This allows residual variance on indicator X4 at T2bf06_25_t2 ~~ res5*bf06_25_t2 # This allows residual variance on indicator X5 at T2bf06_30_t2 ~~ res6*bf06_30_t2 # This allows residual variance on indicator X6 at T2 bf06_35_t2 ~~ res7*bf06_35_t2 # This allows residual variance on indicator X7 at T2 bf06_40_t2 ~~ res8*bf06_40_t2 # This allows residual variance on indicator X8 at T2bf06_45_t2 ~~ res9*bf06_45_t2 # This allows residual variance on indicator X9 at T2bf06_50_t2 ~~ res10*bf06_50_t2 # This allows residual variance on indicator X10 at T2bf06_55_t2 ~~ res11*bf06_55_t2 # This allows residual variance on indicator X11 at T2bf06_60_t2 ~~ res12*bf06_60_t2 # This allows residual variance on indicator X12 at T2bf06_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa06_01_t1 ~~ sa06_01_t1sa06_01_t1 ~ 1'fit_mi_lcs_openn_ideal_hyp5 <-lavaan(mi_lcs_openn_ideal_hyp5, data=df_sbsa_wide_pers_sa, estimator='WLSMV', fixed.x=FALSE, ordered="sa06_01_t1")# This model did not converge properly (when adding the 'sa06_01_t1' goal variable). Declaring 'sa06_01_t1' as an # ordered variable and using the WLSMV estimator (sadly without FIML) worked in the end. Results # https://lavaan.ugent.be/tutorial/cat.htmlsummary(fit_mi_lcs_openn_ideal_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of the general acceptance goal with the openness change score (ideal-self) is significantly different from zero, r = -0.008, p = 0.008. (I had to use the ‘WLSMV’ estimator with the “ordered” argument here to get the model to converge - not sure if this is comparable to the other models since a really small estimate becomes significant here…)
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_curr_specif_hyp5 <-'openn_t1 =~ 1*bf05_05_t1 + lamb2*bf05_10_t1 + lamb3*bf05_15_t1 + lamb4*bf05_20_t1 + lamb5*bf05_25_t1 + lamb6*bf05_30_t1 + lamb7*bf05_35_t1 + lamb8*bf05_40_t1 + lamb9*bf05_45_t1 + lamb10*bf05_50_t1 + lamb11*bf05_55_t1 + lamb12*bf05_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf05_05_t2 + lamb2*bf05_10_t2 + lamb3*bf05_15_t2 + lamb4*bf05_20_t2 + lamb5*bf05_25_t2 + lamb6*bf05_30_t2 + lamb7*bf05_35_t2 + lamb8*bf05_40_t2 + lamb9*bf05_45_t2 + lamb10*bf05_50_t2 + lamb11*bf05_55_t2 + lamb12*bf05_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_13_t1 + sa07_14_t1 + sa07_15_t1 # latent acceptance goal variable (three facets per trait)openn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf05_05_t1 ~~ bf05_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf05_10_t1 ~~ bf05_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf05_15_t1 ~~ bf05_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf05_20_t1 ~~ bf05_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf05_25_t1 ~~ bf05_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf05_30_t1 ~~ bf05_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf05_35_t1 ~~ bf05_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf05_40_t1 ~~ bf05_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf05_45_t1 ~~ bf05_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf05_50_t1 ~~ bf05_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf05_55_t1 ~~ bf05_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf05_60_t1 ~~ bf05_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf05_05_t1 ~~ res1*bf05_05_t1 # This allows residual variance on indicator X1 at T1 bf05_10_t1 ~~ res2*bf05_10_t1 # This allows residual variance on indicator X2 at T1bf05_15_t1 ~~ res3*bf05_15_t1 # This allows residual variance on indicator X3 at T1bf05_20_t1 ~~ res4*bf05_20_t1 # This allows residual variance on indicator X4 at T1bf05_25_t1 ~~ res5*bf05_25_t1 # This allows residual variance on indicator X5 at T1bf05_30_t1 ~~ res6*bf05_30_t1 # This allows residual variance on indicator X6 at T1 bf05_35_t1 ~~ res7*bf05_35_t1 # This allows residual variance on indicator X7 at T1bf05_40_t1 ~~ res8*bf05_40_t1 # This allows residual variance on indicator X8 at T1bf05_45_t1 ~~ res9*bf05_45_t1 # This allows residual variance on indicator X9 at T1bf05_50_t1 ~~ res10*bf05_50_t1 # This allows residual variance on indicator X10 at T1bf05_55_t1 ~~ res11*bf05_55_t1 # This allows residual variance on indicator X11 at T1bf05_60_t1 ~~ res12*bf05_60_t1 # This allows residual variance on indicator X12 at T1bf05_05_t2 ~~ res1*bf05_05_t2 # This allows residual variance on indicator X1 at T2 bf05_10_t2 ~~ res2*bf05_10_t2 # This allows residual variance on indicator X2 at T2 bf05_15_t2 ~~ res3*bf05_15_t2 # This allows residual variance on indicator X3 at T2bf05_20_t2 ~~ res4*bf05_20_t2 # This allows residual variance on indicator X4 at T2bf05_25_t2 ~~ res5*bf05_25_t2 # This allows residual variance on indicator X5 at T2bf05_30_t2 ~~ res6*bf05_30_t2 # This allows residual variance on indicator X6 at T2 bf05_35_t2 ~~ res7*bf05_35_t2 # This allows residual variance on indicator X7 at T2 bf05_40_t2 ~~ res8*bf05_40_t2 # This allows residual variance on indicator X8 at T2bf05_45_t2 ~~ res9*bf05_45_t2 # This allows residual variance on indicator X9 at T2bf05_50_t2 ~~ res10*bf05_50_t2 # This allows residual variance on indicator X10 at T2bf05_55_t2 ~~ res11*bf05_55_t2 # This allows residual variance on indicator X11 at T2bf05_60_t2 ~~ res12*bf05_60_t2 # This allows residual variance on indicator X12 at T2bf05_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf05_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf05_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf05_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf05_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf05_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf05_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf05_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf05_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf05_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf05_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf05_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf05_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf05_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf05_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf05_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf05_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf05_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf05_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf05_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf05_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf05_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf05_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf05_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_13_t1 ~~ sa07_13_t1sa07_14_t1 ~~ sa07_14_t1sa07_15_t1 ~~ sa07_15_t1sa07_13_t1 ~ 1sa07_14_t1 ~ 1sa07_15_t1 ~ 1'fit_mi_lcs_openn_curr_specif_hyp5 <-lavaan(mi_lcs_openn_curr_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')summary(fit_mi_lcs_openn_curr_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with openness change score (current-self) is not significantly different from zero, r = 0.004, p = 0.374.
# adding correlation with latent (made up of the three facets) acceptance goal variable to the latent change score model:# Fit the multiple indicator univariate latent change score modelmi_lcs_openn_ideal_specif_hyp5 <-'openn_t1 =~ 1*bf06_05_t1 + lamb2*bf06_10_t1 + lamb3*bf06_15_t1 + lamb4*bf06_20_t1 + lamb5*bf06_25_t1 + lamb6*bf06_30_t1 + lamb7*bf06_35_t1 + lamb8*bf06_40_t1 + lamb9*bf06_45_t1 + lamb10*bf06_50_t1 + lamb11*bf06_55_t1 + lamb12*bf06_60_t1 # This specifies the measurement model for openn_t1 openn_t2 =~ 1*bf06_05_t2 + lamb2*bf06_10_t2 + lamb3*bf06_15_t2 + lamb4*bf06_20_t2 + lamb5*bf06_25_t2 + lamb6*bf06_30_t2 + lamb7*bf06_35_t2 + lamb8*bf06_40_t2 + lamb9*bf06_45_t2 + lamb10*bf06_50_t2 + lamb11*bf06_55_t2 + lamb12*bf06_60_t2 # This specifies the measurement model for openn_t2 with the equality constrained factor loadingsgoals =~ 1*sa07_13_t1 + sa07_14_t1 + sa07_15_t1 # latent acceptance goal variable (three facets per trait)openn_t2 ~ 1*openn_t1 # This parameter regresses openn_t2 perfectly on openn_t1d_openn_1 =~ 1*openn_t2 # This defines the latent change score factor as measured perfectly by scores on openn_t2openn_t2 ~ 0*1 # This line constrains the intercept of openn_t2 to 0openn_t2 ~~ 0*openn_t2 # This fixes the variance of openn_t2 to 0d_openn_1 ~ 1 # This estimates the intercept of the change score openn_t1 ~ 1 # This estimates the intercept of openn_t1 d_openn_1 ~~ d_openn_1 # This estimates the variance of the change scores openn_t1 ~~ openn_t1 # This estimates the variance of the openn_t1 d_openn_1 ~ openn_t1 # This estimates the self-feedback parameterd_openn_1 ~~ goals # estimates the covariance/correlation with the (latent) acceptance goal variablegoals ~ 0*1 # This fixes the intercept of the (latent) acceptance goal variable to 0goals ~~ goals # This estimates the variance of the (latent) acceptance goal variablebf06_05_t1 ~~ bf06_05_t2 # This allows residual covariance on indicator X1 across T1 and T2bf06_10_t1 ~~ bf06_10_t2 # This allows residual covariance on indicator X2 across T1 and T2bf06_15_t1 ~~ bf06_15_t2 # This allows residual covariance on indicator X3 across T1 and T2bf06_20_t1 ~~ bf06_20_t2 # This allows residual covariance on indicator X4 across T1 and T2bf06_25_t1 ~~ bf06_25_t2 # This allows residual covariance on indicator X5 across T1 and T2bf06_30_t1 ~~ bf06_30_t2 # This allows residual covariance on indicator X6 across T1 and T2bf06_35_t1 ~~ bf06_35_t2 # This allows residual covariance on indicator X7 across T1 and T2bf06_40_t1 ~~ bf06_40_t2 # This allows residual covariance on indicator X8 across T1 and T2bf06_45_t1 ~~ bf06_45_t2 # This allows residual covariance on indicator X9 across T1 and T2bf06_50_t1 ~~ bf06_50_t2 # This allows residual covariance on indicator X10 across T1 and T2bf06_55_t1 ~~ bf06_55_t2 # This allows residual covariance on indicator X11 across T1 and T2bf06_60_t1 ~~ bf06_60_t2 # This allows residual covariance on indicator X12 across T1 and T2bf06_05_t1 ~~ res1*bf06_05_t1 # This allows residual variance on indicator X1 at T1 bf06_10_t1 ~~ res2*bf06_10_t1 # This allows residual variance on indicator X2 at T1bf06_15_t1 ~~ res3*bf06_15_t1 # This allows residual variance on indicator X3 at T1bf06_20_t1 ~~ res4*bf06_20_t1 # This allows residual variance on indicator X4 at T1bf06_25_t1 ~~ res5*bf06_25_t1 # This allows residual variance on indicator X5 at T1bf06_30_t1 ~~ res6*bf06_30_t1 # This allows residual variance on indicator X6 at T1 bf06_35_t1 ~~ res7*bf06_35_t1 # This allows residual variance on indicator X7 at T1bf06_40_t1 ~~ res8*bf06_40_t1 # This allows residual variance on indicator X8 at T1bf06_45_t1 ~~ res9*bf06_45_t1 # This allows residual variance on indicator X9 at T1bf06_50_t1 ~~ res10*bf06_50_t1 # This allows residual variance on indicator X10 at T1bf06_55_t1 ~~ res11*bf06_55_t1 # This allows residual variance on indicator X11 at T1bf06_60_t1 ~~ res12*bf06_60_t1 # This allows residual variance on indicator X12 at T1bf06_05_t2 ~~ res1*bf06_05_t2 # This allows residual variance on indicator X1 at T2 bf06_10_t2 ~~ res2*bf06_10_t2 # This allows residual variance on indicator X2 at T2 bf06_15_t2 ~~ res3*bf06_15_t2 # This allows residual variance on indicator X3 at T2bf06_20_t2 ~~ res4*bf06_20_t2 # This allows residual variance on indicator X4 at T2bf06_25_t2 ~~ res5*bf06_25_t2 # This allows residual variance on indicator X5 at T2bf06_30_t2 ~~ res6*bf06_30_t2 # This allows residual variance on indicator X6 at T2 bf06_35_t2 ~~ res7*bf06_35_t2 # This allows residual variance on indicator X7 at T2 bf06_40_t2 ~~ res8*bf06_40_t2 # This allows residual variance on indicator X8 at T2bf06_45_t2 ~~ res9*bf06_45_t2 # This allows residual variance on indicator X9 at T2bf06_50_t2 ~~ res10*bf06_50_t2 # This allows residual variance on indicator X10 at T2bf06_55_t2 ~~ res11*bf06_55_t2 # This allows residual variance on indicator X11 at T2bf06_60_t2 ~~ res12*bf06_60_t2 # This allows residual variance on indicator X12 at T2bf06_05_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1bf06_10_t1 ~ m2*1 # This estimates the intercept of X2 at T1bf06_15_t1 ~ m3*1 # This estimates the intercept of X3 at T1bf06_20_t1 ~ m4*1 # This estimates the intercept of X4 at T1bf06_25_t1 ~ m5*1 # This estimates the intercept of X5 at T1bf06_30_t1 ~ m6*1 # This estimates the intercept of X6 at T1bf06_35_t1 ~ m7*1 # This estimates the intercept of X7 at T1bf06_40_t1 ~ m8*1 # This estimates the intercept of X8 at T1bf06_45_t1 ~ m9*1 # This estimates the intercept of X9 at T1bf06_50_t1 ~ m10*1 # This estimates the intercept of X10 at T1bf06_55_t1 ~ m11*1 # This estimates the intercept of X11 at T1bf06_60_t1 ~ m12*1 # This estimates the intercept of X12 at T1bf06_05_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2bf06_10_t2 ~ m2*1 # This estimates the intercept of X2 at T2bf06_15_t2 ~ m3*1 # This estimates the intercept of X3 at T2bf06_20_t2 ~ m4*1 # This estimates the intercept of X4 at T2bf06_25_t2 ~ m5*1 # This estimates the intercept of X5 at T2bf06_30_t2 ~ m6*1 # This estimates the intercept of X6 at T2bf06_35_t2 ~ m7*1 # This estimates the intercept of X7 at T2bf06_40_t2 ~ m8*1 # This estimates the intercept of X8 at T2bf06_45_t2 ~ m9*1 # This estimates the intercept of X9 at T2bf06_50_t2 ~ m10*1 # This estimates the intercept of X10 at T2bf06_55_t2 ~ m11*1 # This estimates the intercept of X11 at T2bf06_60_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa07_13_t1 ~~ sa07_13_t1sa07_14_t1 ~~ sa07_14_t1sa07_15_t1 ~~ sa07_15_t1sa07_13_t1 ~ 1sa07_14_t1 ~ 1sa07_15_t1 ~ 1'fit_mi_lcs_openn_ideal_specif_hyp5 <-lavaan(mi_lcs_openn_ideal_specif_hyp5, data=df_sbsa_wide_pers_sa, estimator='WLSMV', fixed.x=FALSE, ordered=c("sa07_13_t1", "sa07_14_t1", "sa07_15_t1"))# This model did not converge properly (when adding the 'sa06_01_t1' goal variable). Declaring 'sa06_01_t1' as an # ordered variable and using the WLSMV estimator (sadly without FIML) worked in the end. Results # https://lavaan.ugent.be/tutorial/cat.htmlsummary(fit_mi_lcs_openn_ideal_specif_hyp5, fit.measures=TRUE, standardized=TRUE, rsquare=F)
Results summary (goals = trait/facet specific acceptance goal):
The correlation of specific, facet-level acceptance goals with the openness change score (ideal-self) is significantly different from zero, r = 0.004, p = 0.044. (I had to use the ‘WLSMV’ estimator with the “ordered” argument here to get the model to converge - not sure if this is comparable to the other models since a really small estimate becomes significant here…)
3.7.2 Big Five facets
Run models for all facets with a template & loop:
Show the code
# create template:facet_template <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)facet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 d_facet_1 ~ facet_t1 # This estimates the self-feedback parameterd_facet_1 ~~ ind_goal # estimates the covariance/correlation with acceptance goal variableind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind_goal ~~ ind_goalind_goal ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# loop across 2 BFI versions (combined pre&post current/ideal)for (j in5:length(bfi_versions)) { items =paste0(bfi_versions[[j]], item_nrs)# loop across 2 different goal operationalizations (sa06_01_t1 & sa07_XX_t1)for (k in1:2) {if (k==1) { goal_op ="sa06_01_t1" } else{ goal_op =paste0("sa07_", str_pad(i-5, 2, pad ="0"), "_t1") } template_filled <-str_replace_all(facet_template, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4],"ind_goal"= goal_op)) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sa, estimator='mlr', fixed.x=FALSE, missing='fiml')# save to environmentif (k==1) {eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_hyp5")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_hyp5")), facet_model_fit)) } else{eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_specif_hyp5")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[j], 6), "_specif_hyp5")), facet_model_fit)) } } }}
3.7.2.1 Sociability - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of the general acceptance goal with the sociability change score (current-self) is significantly different from zero, r = 0.057, p = 0.041.
3.7.2.2 Sociability - ideal-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with sociability change score (current-self) is not significantly different from zero, r = -0.007, p = 0.886.
Correlation of specific, facet-level acceptance goals with anxiety change score (ideal-self) is not significantly different from zero, r = -0.047, p = 0.311.
3.7.2.5 Assertiveness - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with assertiveness change score (current-self) is not significantly different from zero, r = -0.004, p = 0.92.
Correlation of specific, facet-level acceptance goals with assertiveness change score (ideal-self) is not significantly different from zero, r = -0.019, p = 0.439.
3.7.2.9 Energy - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with energy change score (current-self) is not significantly different from zero, r = 0.041, p = 0.22.
3.7.2.12 Energy - ideal-self: specific, facet-level acceptance goals
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
Correlation of specific, facet-level acceptance goals with energy change score (ideal-self) is not significantly different from zero, r = 0.021, p = 0.33.
3.7.2.13 Compassion - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with compassion change score (current-self) is not significantly different from zero, r = 0.027, p = 0.563.
Correlation of specific, facet-level acceptance goals with compassion change score (ideal-self) is not significantly different from zero, r = -0.06, p = 0.232.
3.7.2.17 Respectfulness - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with respectfulness change score (current-self) is not significantly different from zero, r = 0.004, p = 0.884.
Correlation of specific, facet-level acceptance goals with respectfulness change score (ideal-self) is not significantly different from zero, r = -0.021, p = 0.461.
3.7.2.21 Trust - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with trust change score (current-self) is not significantly different from zero, r = 0.055, p = 0.101.
Correlation of specific, facet-level acceptance goals with trust change score (ideal-self) is not significantly different from zero, r = 0.026, p = 0.455.
3.7.2.25 Organization - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of specific, facet-level acceptance goals with the organization change score (current-self) is significantly different from zero, r = 0.162, p = 0.017.
Correlation of specific, facet-level acceptance goals with organization change score (ideal-self) is not significantly different from zero, r = 0.041, p = 0.198.
3.7.2.29 Productiveness - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of general acceptance goal with productiveness change score (current-self) is not significantly different from zero, r = -0.011, p = 0.679.
3.7.2.30 Productiveness - ideal-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with productiveness change score (current-self) is not significantly different from zero, r = 0.09, p = 0.132.
Correlation of specific, facet-level acceptance goals with productiveness change score (ideal-self) is not significantly different from zero, r = 0.011, p = 0.71.
3.7.2.33 Responsibility - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of specific, facet-level acceptance goals with the responsibility change score (current-self) is significantly different from zero, r = -0.168, p = 0.001.
Correlation of specific, facet-level acceptance goals with responsibility change score (ideal-self) is not significantly different from zero, r = -0.047, p = 0.314.
3.7.2.37 Anxiety - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with anxiety change score (current-self) is not significantly different from zero, r = -0.012, p = 0.851.
Correlation of specific, facet-level acceptance goals with anxiety change score (ideal-self) is not significantly different from zero, r = -0.007, p = 0.894.
3.7.2.41 Depression - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with depression change score (current-self) is not significantly different from zero, r = -0.056, p = 0.361.
Correlation of specific, facet-level acceptance goals with depression change score (ideal-self) is not significantly different from zero, r = -0.028, p = 0.257.
3.7.2.45 Volatility - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with volatility change score (current-self) is not significantly different from zero, r = -0.011, p = 0.855.
Correlation of specific, facet-level acceptance goals with volatility change score (ideal-self) is not significantly different from zero, r = -0.01, p = 0.8.
3.7.2.49 Curiosity - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
The correlation of specific, facet-level acceptance goals with the curiosity change score (current-self) is significantly different from zero, r = -0.119, p = 0.012.
Correlation of specific, facet-level acceptance goals with curiosity change score (ideal-self) is not significantly different from zero, r = -0.066, p = 0.055.
3.7.2.53 Aesthetic - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with aesthetic change score (current-self) is not significantly different from zero, r = -0.001, p = 0.729.
Correlation of specific, facet-level acceptance goals with aesthetic change score (ideal-self) is not significantly different from zero, r = -0.006, p = 0.461.
3.7.2.57 Imagination - current-self: general acceptance goals
Results summary (sa06_01_t1 = general acceptance goal):
Correlation of specific, facet-level acceptance goals with imagination change score (current-self) is not significantly different from zero, r = -0.06, p = 0.201.
Correlation of specific, facet-level acceptance goals with imagination change score (ideal-self) is not significantly different from zero, r = 0.006, p = 0.87.
Results summary across the Big Five traits: covariance of the latent change score and acceptance goal(s)
kable(df_table_hyp5[1:20, ], digits =3)
trait
ref
goal
estimate
std.all
statistic
p.value
extraversion
current
general
0.059
0.138
2.234
0.025
extraversion
ideal
general
0.024
0.122
1.629
0.103
extraversion
current
specific
0.041
0.106
0.960
0.337
extraversion
ideal
specific
-0.024
-0.135
-1.087
0.277
agreeableness
current
general
0.021
0.070
0.776
0.438
agreeableness
ideal
general
0.017
0.050
0.654
0.513
agreeableness
current
specific
0.011
0.044
0.517
0.605
agreeableness
ideal
specific
-0.009
-0.030
-0.332
0.740
conscientiousness
current
general
0.004
0.009
0.137
0.891
conscientiousness
ideal
general
0.002
0.008
0.108
0.914
conscientiousness
current
specific
0.141
0.257
2.308
0.021
conscientiousness
ideal
specific
0.034
0.114
1.422
0.155
neuroticism
current
general
0.056
0.120
1.647
0.100
neuroticism
ideal
general
0.023
0.101
1.415
0.157
neuroticism
current
specific
-0.035
-0.082
-0.894
0.371
neuroticism
ideal
specific
-0.041
-0.212
-3.056
0.002
openness
current
general
-0.003
-0.067
-0.791
0.429
openness
ideal
general
-0.008
-0.272
-2.646
0.008
openness
current
specific
0.004
0.116
0.889
0.374
openness
ideal
specific
0.004
0.200
2.016
0.044
Five covariances significantly differ from zero:
changes in current-level neuroticism covary with the general acceptance goal
changes in current-level conscientiousness covary with the specific acceptance goals (latent factor of the three C facets)
changes in ideal-level neuroticism covary with the specific acceptance goals (latent factor of the three N facets)
changes in ideal-level openness covary with the general acceptance goal
changes in ideal-level openness covary with the specific acceptance goals (latent factor of the three O facets)
Results summary across the Big Five facets: covariance of the latent change score and acceptance goal(s)
kable(df_table_hyp5[21:80, ], digits =3)
trait
ref
goal
estimate
std.all
statistic
p.value
sociability
current
general
0.057
0.160
2.042
0.041
sociability
ideal
general
0.003
0.011
0.132
0.895
sociability
current
specific
-0.007
-0.013
-0.143
0.886
sociability
ideal
specific
-0.047
-0.136
-1.014
0.311
assertiveness
current
general
0.041
0.135
1.624
0.104
assertiveness
ideal
general
0.020
0.114
1.198
0.231
assertiveness
current
specific
-0.004
-0.009
-0.100
0.920
assertiveness
ideal
specific
-0.019
-0.074
-0.773
0.439
energy
current
general
-0.011
-0.043
-0.597
0.551
energy
ideal
general
-0.020
-0.177
-1.232
0.218
energy
current
specific
0.041
0.113
1.226
0.220
energy
ideal
specific
0.021
0.129
0.975
0.330
compassion
current
general
0.085
0.201
1.935
0.053
compassion
ideal
general
0.043
0.116
1.128
0.259
compassion
current
specific
0.027
0.048
0.578
0.563
compassion
ideal
specific
-0.060
-0.120
-1.195
0.232
respectfulness
current
general
0.017
0.071
0.737
0.461
respectfulness
ideal
general
0.002
0.007
0.078
0.938
respectfulness
current
specific
0.004
0.013
0.146
0.884
respectfulness
ideal
specific
-0.021
-0.069
-0.738
0.461
trust
current
general
-0.003
-0.010
-0.108
0.914
trust
ideal
general
-0.039
-0.148
-1.579
0.114
trust
current
specific
0.055
0.142
1.639
0.101
trust
ideal
specific
0.026
0.068
0.747
0.455
organization
current
general
0.022
0.055
0.692
0.489
organization
ideal
general
0.011
0.052
0.599
0.549
organization
current
specific
0.162
0.248
2.390
0.017
organization
ideal
specific
0.041
0.117
1.288
0.198
productiveness
current
general
-0.011
-0.032
-0.413
0.679
productiveness
ideal
general
-0.019
-0.084
-0.929
0.353
productiveness
current
specific
0.090
0.170
1.504
0.132
productiveness
ideal
specific
0.011
0.034
0.371
0.710
responsibility
current
general
0.018
0.079
0.680
0.496
responsibility
ideal
general
0.010
0.028
0.291
0.771
responsibility
current
specific
-0.168
-0.447
-3.336
0.001
responsibility
ideal
specific
-0.047
-0.089
-1.008
0.314
anxiety
current
general
0.017
0.043
0.442
0.658
anxiety
ideal
general
0.029
0.102
1.198
0.231
anxiety
current
specific
-0.012
-0.020
-0.188
0.851
anxiety
ideal
specific
-0.007
-0.017
-0.133
0.894
depression
current
general
0.013
0.036
0.462
0.644
depression
ideal
general
0.007
0.047
0.473
0.636
depression
current
specific
-0.056
-0.097
-0.913
0.361
depression
ideal
specific
-0.028
-0.121
-1.134
0.257
volatility
current
general
-0.068
-0.142
-1.701
0.089
volatility
ideal
general
-0.065
-0.178
-2.077
0.038
volatility
current
specific
-0.011
-0.017
-0.183
0.855
volatility
ideal
specific
-0.010
-0.021
-0.253
0.800
curiosity
current
general
0.011
0.035
0.387
0.699
curiosity
ideal
general
0.024
0.115
1.177
0.239
curiosity
current
specific
-0.119
-0.265
-2.508
0.012
curiosity
ideal
specific
-0.066
-0.222
-1.917
0.055
aesthetic
current
general
-0.003
-0.116
-1.498
0.134
aesthetic
ideal
general
0.003
0.074
0.735
0.462
aesthetic
current
specific
-0.001
-0.028
-0.347
0.729
aesthetic
ideal
specific
-0.006
-0.097
-0.738
0.461
imagination
current
general
0.026
0.086
0.861
0.389
imagination
ideal
general
-0.014
-0.058
-0.585
0.559
imagination
current
specific
-0.060
-0.128
-1.278
0.201
imagination
ideal
specific
0.006
0.015
0.163
0.870
Looking at the facets, we find five covariances that significantly differ from zero (relatively unsystematic across facets / current-ideal / goal dimension): Changes in current-level sociability covary with the general acceptance goal. Further, changes in current-level organization, responsibility, and curiosity covary with the respective specific facet acceptance goal. Lastly, for ideal-level personality, only changes in volatility covary with the general acceptance goal.
3.8 Hypothesis 6: Desire to change and frequency of skill-building behaviors as moderators of change in personality in skill-building group
Desire to change and frequency of skill-building behaviors measured at the follow-up assessment will be positively related to change in current-self ratings in the skill-building group.
To test this hypothesis, we will estimate the mean-level difference in current trait ratings between baseline and follow up using a latent change model for each big five domain and facet. We will then include two moderators. The first will indicate how much the individual wanted to change on a given big five domain or facet. The second will indicate their frequency of skill-building behaviors. We will estimate the main effects of each of these variables and the interaction between these variables on the trait change score.
Reshape and split data set by intervention group:
Show the code
df_sbsa_wide_pers_sb_mod <- df_sbsa %>%filter(rando=="Skill-Building") %>%arrange(pid, time) %>%select(pid, time, starts_with(c("bf05", # only need current-level"sb07", # facet-specific change goals"sb04"))) %>%# frequency skill-building behaviorspivot_wider(names_from = time,names_sep ="_t",values_from =c(starts_with(c("bf05", "sb07", "sb04")))) %>%select(-c(sb07_01_t2, sb07_02_t2, sb07_03_t2, sb07_04_t2, sb07_05_t2, sb07_06_t2, sb07_07_t2, sb07_08_t2, sb07_09_t2, sb07_10_t2, sb07_11_t2, sb07_12_t2, sb07_13_t2, sb07_14_t2, sb07_15_t2, sb04_01_t1, sb04_02_t1, sb04_03_t1)) # frequency of skill-building behaviors measured at T2colnames(df_sbsa_wide_pers_sb_mod)
3.8.1 Big Five traits
Run models for all traits with a template & loop:
Show the code
# create templates:# 1st, for facet-specific change goalstrait_template_mod_goal <-'trait_t1 =~ 1*ind01_t1 + lamb2*ind02_t1 + lamb3*ind03_t1 + lamb4*ind04_t1 + lamb5*ind05_t1 + lamb6*ind06_t1 + lamb7*ind07_t1 + lamb8*ind08_t1 + lamb9*ind09_t1 + lamb10*ind10_t1 + lamb11*ind11_t1 + lamb12*ind12_t1 # This specifies the measurement model for trait_t1 trait_t2 =~ 1*ind01_t2 + lamb2*ind02_t2 + lamb3*ind03_t2 + lamb4*ind04_t2 + lamb5*ind05_t2 + lamb6*ind06_t2 + lamb7*ind07_t2 + lamb8*ind08_t2 + lamb9*ind09_t2 + lamb10*ind10_t2 + lamb11*ind11_t2 + lamb12*ind12_t2 # This specifies the measurement model for trait_t2 with the equality constrained factor loadingsgoals =~ 1*ind_goal_1 + ind_goal_2 + ind_goal_3 # latent variable for moderatortrait_t2 ~ 1*trait_t1 # This parameter regresses trait_t2 perfectly on trait_t1d_trait_1 =~ 1*trait_t2 # This defines the latent change score factor as measured perfectly by scores on trait_t2trait_t2 ~ 0*1 # This line constrains the intercept of trait_t2 to 0trait_t2 ~~ 0*trait_t2 # This fixes the variance of trait_t2 to 0d_trait_1 ~ 1 # This estimates the intercept of the change score trait_t1 ~ 1 # This estimates the intercept of trait_t1 d_trait_1 ~~ d_trait_1 # This estimates the variance of the change scores trait_t1 ~~ trait_t1 # This estimates the variance of trait_t1 trait_t1 ~ goals # This estimates the moderation effect on personality at T1d_trait_1 ~ trait_t1 + goals # This estimates the self-feedback parameter and the moderation effect on the change scoregoals ~ 0*1 # This fixes the intercept of the moderator to 0goals ~~ goals # This estimates the variance of the moderatorind01_t1 ~~ ind01_t2 # This allows residual covariance on indicator X1 across T1 and T2ind02_t1 ~~ ind02_t2 # This allows residual covariance on indicator X2 across T1 and T2ind03_t1 ~~ ind03_t2 # This allows residual covariance on indicator X3 across T1 and T2ind04_t1 ~~ ind04_t2 # This allows residual covariance on indicator X4 across T1 and T2ind05_t1 ~~ ind05_t2 # This allows residual covariance on indicator X5 across T1 and T2ind06_t1 ~~ ind06_t2 # This allows residual covariance on indicator X6 across T1 and T2ind07_t1 ~~ ind07_t2 # This allows residual covariance on indicator X7 across T1 and T2ind08_t1 ~~ ind08_t2 # This allows residual covariance on indicator X8 across T1 and T2ind09_t1 ~~ ind09_t2 # This allows residual covariance on indicator X9 across T1 and T2ind10_t1 ~~ ind10_t2 # This allows residual covariance on indicator X10 across T1 and T2ind11_t1 ~~ ind11_t2 # This allows residual covariance on indicator X11 across T1 and T2ind12_t1 ~~ ind12_t2 # This allows residual covariance on indicator X12 across T1 and T2ind01_t1 ~~ res1*ind01_t1 # This allows residual variance on indicator X1 at T1 ind02_t1 ~~ res2*ind02_t1 # This allows residual variance on indicator X2 at T1ind03_t1 ~~ res3*ind03_t1 # This allows residual variance on indicator X3 at T1ind04_t1 ~~ res4*ind04_t1 # This allows residual variance on indicator X4 at T1ind05_t1 ~~ res5*ind05_t1 # This allows residual variance on indicator X5 at T1ind06_t1 ~~ res6*ind06_t1 # This allows residual variance on indicator X6 at T1 ind07_t1 ~~ res7*ind07_t1 # This allows residual variance on indicator X7 at T1ind08_t1 ~~ res8*ind08_t1 # This allows residual variance on indicator X8 at T1ind09_t1 ~~ res9*ind09_t1 # This allows residual variance on indicator X9 at T1ind10_t1 ~~ res10*ind10_t1 # This allows residual variance on indicator X10 at T1ind11_t1 ~~ res11*ind11_t1 # This allows residual variance on indicator X11 at T1ind12_t1 ~~ res12*ind12_t1 # This allows residual variance on indicator X12 at T1ind01_t2 ~~ res1*ind01_t2 # This allows residual variance on indicator X1 at T2 ind02_t2 ~~ res2*ind02_t2 # This allows residual variance on indicator X2 at T2 ind03_t2 ~~ res3*ind03_t2 # This allows residual variance on indicator X3 at T2ind04_t2 ~~ res4*ind04_t2 # This allows residual variance on indicator X4 at T2ind05_t2 ~~ res5*ind05_t2 # This allows residual variance on indicator X5 at T2ind06_t2 ~~ res6*ind06_t2 # This allows residual variance on indicator X6 at T2 ind07_t2 ~~ res7*ind07_t2 # This allows residual variance on indicator X7 at T2 ind08_t2 ~~ res8*ind08_t2 # This allows residual variance on indicator X8 at T2ind09_t2 ~~ res9*ind09_t2 # This allows residual variance on indicator X9 at T2ind10_t2 ~~ res10*ind10_t2 # This allows residual variance on indicator X10 at T2ind11_t2 ~~ res11*ind11_t2 # This allows residual variance on indicator X11 at T2ind12_t2 ~~ res12*ind12_t2 # This allows residual variance on indicator X12 at T2ind01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind02_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind03_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind04_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind05_t1 ~ m5*1 # This estimates the intercept of X5 at T1ind06_t1 ~ m6*1 # This estimates the intercept of X6 at T1ind07_t1 ~ m7*1 # This estimates the intercept of X7 at T1ind08_t1 ~ m8*1 # This estimates the intercept of X8 at T1ind09_t1 ~ m9*1 # This estimates the intercept of X9 at T1ind10_t1 ~ m10*1 # This estimates the intercept of X10 at T1ind11_t1 ~ m11*1 # This estimates the intercept of X11 at T1ind12_t1 ~ m12*1 # This estimates the intercept of X12 at T1ind01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind02_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind03_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind04_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind05_t2 ~ m5*1 # This estimates the intercept of X5 at T2ind06_t2 ~ m6*1 # This estimates the intercept of X6 at T2ind07_t2 ~ m7*1 # This estimates the intercept of X7 at T2ind08_t2 ~ m8*1 # This estimates the intercept of X8 at T2ind09_t2 ~ m9*1 # This estimates the intercept of X9 at T2ind10_t2 ~ m10*1 # This estimates the intercept of X10 at T2ind11_t2 ~ m11*1 # This estimates the intercept of X11 at T2ind12_t2 ~ m12*1 # This estimates the intercept of X12 at T2ind_goal_1 ~~ ind_goal_1ind_goal_2 ~~ ind_goal_2ind_goal_3 ~~ ind_goal_3ind_goal_1 ~ 1ind_goal_2 ~ 1ind_goal_3 ~ 1'trait_facets_nrs <-list(a1 =c(1:3), b2 =c(4:6), c3 =c(7:9), d4 =c(10:12), e5 =c(13:15)) # matching facet nrs to traits # loop across 5 traitsfor (i in1:5) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post current items =paste0(bfi_versions[[5]], item_nrs) mod_names =paste0("sb07_", str_pad(trait_facets_nrs[[i]], 2, pad ="0"), "_t1") template_filled <-str_replace_all(trait_template_mod_goal, c("trait"= short_name,"ind01"= items[1], "ind02"= items[2], "ind03"= items[3], "ind04"= items[4],"ind05"= items[5], "ind06"= items[6], "ind07"= items[7], "ind08"= items[8],"ind09"= items[9], "ind10"= items[10], "ind11"= items[11], "ind12"= items[12],"ind_goal_1"= mod_names[1], "ind_goal_2"= mod_names[2], "ind_goal_3"= mod_names[3])) trait_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sb_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_specif_hyp6")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_specif_hyp6")), trait_model_fit))} # 2nd, for frequency of skill-building behaviortrait_template_mod_frequ <-'trait_t1 =~ 1*ind01_t1 + lamb2*ind02_t1 + lamb3*ind03_t1 + lamb4*ind04_t1 + lamb5*ind05_t1 + lamb6*ind06_t1 + lamb7*ind07_t1 + lamb8*ind08_t1 + lamb9*ind09_t1 + lamb10*ind10_t1 + lamb11*ind11_t1 + lamb12*ind12_t1 # This specifies the measurement model for extra_t1 trait_t2 =~ 1*ind01_t2 + lamb2*ind02_t2 + lamb3*ind03_t2 + lamb4*ind04_t2 + lamb5*ind05_t2 + lamb6*ind06_t2 + lamb7*ind07_t2 + lamb8*ind08_t2 + lamb9*ind09_t2 + lamb10*ind10_t2 + lamb11*ind11_t2 + lamb12*ind12_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsfrequ =~ 1*sb04_01_t2 + sb04_02_t2 + sb04_03_t2 # latent variable for moderatortrait_t2 ~ 1*trait_t1 # This parameter regresses trait_t2 perfectly on trait_t1d_trait_1 =~ 1*trait_t2 # This defines the latent change score factor as measured perfectly by scores on trait_t2trait_t2 ~ 0*1 # This line constrains the intercept of trait_t2 to 0trait_t2 ~~ 0*trait_t2 # This fixes the variance of trait_t2 to 0d_trait_1 ~ 1 # This estimates the intercept of the change score trait_t1 ~ 1 # This estimates the intercept of trait_t1 d_trait_1 ~~ d_trait_1 # This estimates the variance of the change scores trait_t1 ~~ trait_t1 # This estimates the variance of trait_t1 trait_t1 ~ frequ # This estimates the moderation effect on personality at T1d_trait_1 ~ trait_t1 + frequ # This estimates the self-feedback parameter and the moderation effect on the change scorefrequ ~ 0*1 # This fixes the intercept of the moderator to 0frequ ~~ frequ # This estimates the variance of the moderatorind01_t1 ~~ ind01_t2 # This allows residual covariance on indicator X1 across T1 and T2ind02_t1 ~~ ind02_t2 # This allows residual covariance on indicator X2 across T1 and T2ind03_t1 ~~ ind03_t2 # This allows residual covariance on indicator X3 across T1 and T2ind04_t1 ~~ ind04_t2 # This allows residual covariance on indicator X4 across T1 and T2ind05_t1 ~~ ind05_t2 # This allows residual covariance on indicator X5 across T1 and T2ind06_t1 ~~ ind06_t2 # This allows residual covariance on indicator X6 across T1 and T2ind07_t1 ~~ ind07_t2 # This allows residual covariance on indicator X7 across T1 and T2ind08_t1 ~~ ind08_t2 # This allows residual covariance on indicator X8 across T1 and T2ind09_t1 ~~ ind09_t2 # This allows residual covariance on indicator X9 across T1 and T2ind10_t1 ~~ ind10_t2 # This allows residual covariance on indicator X10 across T1 and T2ind11_t1 ~~ ind11_t2 # This allows residual covariance on indicator X11 across T1 and T2ind12_t1 ~~ ind12_t2 # This allows residual covariance on indicator X12 across T1 and T2ind01_t1 ~~ res1*ind01_t1 # This allows residual variance on indicator X1 at T1 ind02_t1 ~~ res2*ind02_t1 # This allows residual variance on indicator X2 at T1ind03_t1 ~~ res3*ind03_t1 # This allows residual variance on indicator X3 at T1ind04_t1 ~~ res4*ind04_t1 # This allows residual variance on indicator X4 at T1ind05_t1 ~~ res5*ind05_t1 # This allows residual variance on indicator X5 at T1ind06_t1 ~~ res6*ind06_t1 # This allows residual variance on indicator X6 at T1 ind07_t1 ~~ res7*ind07_t1 # This allows residual variance on indicator X7 at T1ind08_t1 ~~ res8*ind08_t1 # This allows residual variance on indicator X8 at T1ind09_t1 ~~ res9*ind09_t1 # This allows residual variance on indicator X9 at T1ind10_t1 ~~ res10*ind10_t1 # This allows residual variance on indicator X10 at T1ind11_t1 ~~ res11*ind11_t1 # This allows residual variance on indicator X11 at T1ind12_t1 ~~ res12*ind12_t1 # This allows residual variance on indicator X12 at T1ind01_t2 ~~ res1*ind01_t2 # This allows residual variance on indicator X1 at T2 ind02_t2 ~~ res2*ind02_t2 # This allows residual variance on indicator X2 at T2 ind03_t2 ~~ res3*ind03_t2 # This allows residual variance on indicator X3 at T2ind04_t2 ~~ res4*ind04_t2 # This allows residual variance on indicator X4 at T2ind05_t2 ~~ res5*ind05_t2 # This allows residual variance on indicator X5 at T2ind06_t2 ~~ res6*ind06_t2 # This allows residual variance on indicator X6 at T2 ind07_t2 ~~ res7*ind07_t2 # This allows residual variance on indicator X7 at T2 ind08_t2 ~~ res8*ind08_t2 # This allows residual variance on indicator X8 at T2ind09_t2 ~~ res9*ind09_t2 # This allows residual variance on indicator X9 at T2ind10_t2 ~~ res10*ind10_t2 # This allows residual variance on indicator X10 at T2ind11_t2 ~~ res11*ind11_t2 # This allows residual variance on indicator X11 at T2ind12_t2 ~~ res12*ind12_t2 # This allows residual variance on indicator X12 at T2ind01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind02_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind03_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind04_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind05_t1 ~ m5*1 # This estimates the intercept of X5 at T1ind06_t1 ~ m6*1 # This estimates the intercept of X6 at T1ind07_t1 ~ m7*1 # This estimates the intercept of X7 at T1ind08_t1 ~ m8*1 # This estimates the intercept of X8 at T1ind09_t1 ~ m9*1 # This estimates the intercept of X9 at T1ind10_t1 ~ m10*1 # This estimates the intercept of X10 at T1ind11_t1 ~ m11*1 # This estimates the intercept of X11 at T1ind12_t1 ~ m12*1 # This estimates the intercept of X12 at T1ind01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind02_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind03_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind04_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind05_t2 ~ m5*1 # This estimates the intercept of X5 at T2ind06_t2 ~ m6*1 # This estimates the intercept of X6 at T2ind07_t2 ~ m7*1 # This estimates the intercept of X7 at T2ind08_t2 ~ m8*1 # This estimates the intercept of X8 at T2ind09_t2 ~ m9*1 # This estimates the intercept of X9 at T2ind10_t2 ~ m10*1 # This estimates the intercept of X10 at T2ind11_t2 ~ m11*1 # This estimates the intercept of X11 at T2ind12_t2 ~ m12*1 # This estimates the intercept of X12 at T2sb04_01_t2 ~~ sb04_01_t2sb04_02_t2 ~~ sb04_02_t2sb04_03_t2 ~~ sb04_03_t2sb04_01_t2 ~ 1sb04_02_t2 ~ 1sb04_03_t2 ~ 1'# loop across 5 traitsfor (i in1:5) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post current items =paste0(bfi_versions[[5]], item_nrs) template_filled <-str_replace_all(trait_template_mod_frequ, c("trait"= short_name,"ind01"= items[1], "ind02"= items[2], "ind03"= items[3], "ind04"= items[4],"ind05"= items[5], "ind06"= items[6], "ind07"= items[7], "ind08"= items[8],"ind09"= items[9], "ind10"= items[10], "ind11"= items[11], "ind12"= items[12])) trait_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sb_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_frequ_hyp6")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_frequ_hyp6")), trait_model_fit))}
3.8.1.1 Extraversion: specific, facet-level change goals as moderator of change
Results summary (goals = trait/facet specific change goal):
The moderation effect of specific, facet-level change goals with the extraversion change score (current-self) is not significantly different from zero, b = 0.093, p = 0.378.
3.8.1.2 Extraversion: frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of the frequency of skill-building behaviors with the extraversion change score (current-self) is not significantly different from zero, b = 0.112, p = 0.117.
3.8.1.3 Agreeableness: specific, facet-level change goals as moderator of change
Results summary (goals = trait/facet specific change goal):
The moderation effect of specific, facet-level change goals with the agreeableness change score (current-self) is not significantly different from zero, b = 0.036, p = 0.241.
3.8.1.4 Agreeableness: frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of specific, facet-level change goals with the conscientiousness change score (current-self) is not significantly different from zero, b = -0.036, p = 0.406.
3.8.1.6 Conscientiousness: frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The frequency of skill-building behaviors significantly moderates changes in conscientiousness (current-self), b = -0.146, p = 0.008, although in an unexpected direction such that more frequent skill-building behaviors are associated with more pronounced decreases in conscientiousness.
3.8.1.7 Neuroticism: specific, facet-level change goals as moderator of change
Results summary (goals = trait/facet specific change goal):
The moderation effect of specific, facet-level change goals with the neuroticism change score (current-self) is not significantly different from zero, b = -0.073, p = 0.197.
3.8.1.8 Neuroticism: frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of the frequency of skill-building behaviors with the neuroticism change score (current-self) is not significantly different from zero, b = 0.062, p = 0.286.
3.8.1.9 Openness: specific, facet-level change goals as moderator of change
Results summary (goals = trait/facet specific change goal):
The frequency of skill-building behaviors significantly moderates changes in openness (current-self), b = 0.01, p = 0.039.
3.8.2 Big Five facets
Run models for all facets with a template & loop:
Show the code
# create templates:# 1st, for facet-specific change goalfacet_template_mod_goal <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)facet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 facet_t1 ~ ind_goal # This estimates the moderation effect on personality at T1d_facet_1 ~ facet_t1 + ind_goal # This estimates the self-feedback parameter and the moderation effect on the change scoreind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind_goal ~~ ind_goalind_goal ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post current items =paste0(bfi_versions[[5]], item_nrs) mod_name =paste0("sb07_", str_pad(i-5, 2, pad ="0"), "_t1") template_filled <-str_replace_all(facet_template_mod_goal, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4],"ind_goal"= mod_name)) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sb_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_specif_hyp6")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_specif_hyp6")), facet_model_fit))} # 2nd, for frequency of skill-building behaviorfacet_template_mod_frequ <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)frequ =~ 1*sb04_01_t2 + sb04_02_t2 + sb04_03_t2 # latent variable for moderatorfacet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 facet_t1 ~ frequ # This estimates the moderation effect on personality at T1d_facet_1 ~ facet_t1 + frequ # This estimates the self-feedback parameter and the moderation effect on the change scorefrequ ~ 0*1 # This fixes the intercept of the moderator to 0frequ ~~ frequ # This estimates the variance of the moderatorind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2sb04_01_t2 ~~ sb04_01_t2sb04_02_t2 ~~ sb04_02_t2sb04_03_t2 ~~ sb04_03_t2sb04_01_t2 ~ 1sb04_02_t2 ~ 1sb04_03_t2 ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post current items =paste0(bfi_versions[[5]], item_nrs) template_filled <-str_replace_all(facet_template_mod_frequ, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4])) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sb_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_frequ_hyp6")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[5], 6), "_frequ_hyp6")), facet_model_fit))}
3.8.2.1 Sociability - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the sociability change score (current-self) is not significantly different from zero, b = -0.006, p = 0.871.
3.8.2.2 Sociability - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with sociability change score (ideal-self) is not significantly different from zero, b = 0.051, p = 0.438.
3.8.2.3 Assertiveness - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the assertiveness change score (current-self) is not significantly different from zero, b = 0.036, p = 0.214.
3.8.2.4 Assertiveness - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the assertiveness change score (ideal-self) is not significantly different from zero, b = 0.065, p = 0.175.
3.8.2.5 Energy - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the energy change score (current-self) is not significantly different from zero, b = -0.002, p = 0.886.
3.8.2.6 Energy - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the energy change score (ideal-self) is not significantly different from zero, b = -0.06, p = 0.135.
3.8.2.7 Compassion - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the compassion change score (current-self) is not significantly different from zero, b = 0.017, p = 0.495.
3.8.2.8 Compassion - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the facet-specific change goal with the respectfulness change score (current-self) is not significantly different from zero, b = 0.037, p = 0.141.
3.8.2.10 Respectfulness - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the facet-specific change goal with the trust change score (current-self) is not significantly different from zero, b = -0.023, p = 0.373.
3.8.2.12 Trust - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the facet-specific change goal with the organization change score (current-self) is not significantly different from zero, b = -0.027, p = 0.491.
3.8.2.14 Organization - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the facet-specific change goal with the productiveness change score (current-self) is not significantly different from zero, b = -0.033, p = 0.254.
3.8.2.16 Productiveness - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the facet-specific change goal with the responsibility change score (current-self) is not significantly different from zero, b = 0.003, p = 0.854.
3.8.2.18 Responsibility - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the responsibility change score (ideal-self) is not significantly different from zero, b = 0.027, p = 0.435.
3.8.2.19 Anxiety - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the anxiety change score (current-self) is not significantly different from zero, b = -0.053, p = 0.194.
3.8.2.20 Anxiety - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the anxiety change score (ideal-self) is not significantly different from zero, b = 0.069, p = 0.365.
3.8.2.21 Depression - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the depression change score (current-self) is not significantly different from zero, b = -0.024, p = 0.416.
3.8.2.22 Depression - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the depression change score (ideal-self) is not significantly different from zero, b = 0.02, p = 0.661.
3.8.2.23 Volatility - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the volatility change score (current-self) is not significantly different from zero, b = -0.03, p = 0.368.
3.8.2.24 Volatility - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the volatility change score (ideal-self) is significantly different from zero, b = -0.063, p = 0.339.
3.8.2.25 Curiosity - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the curiosity change score (current-self) is not significantly different from zero, b = 0.002, p = 0.943.
3.8.2.26 Curiosity - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the curiosity change score (ideal-self) is not significantly different from zero, b = 0.097, p = 0.062.
3.8.2.27 Aesthetic - specific, facet-level change goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the aesthetic change score (current-self) is not significantly different from zero, b = 0.003, p = 0.068.
3.8.2.28 Aesthetic - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the aesthetic change score (ideal-self) is not significantly different from zero, b = 0.006, p = 0.067.
3.8.2.29 Imagination - specific, facet-level change goal as moderator of change
Results summary (*sb07_$$_t1* = trait/facet specific acceptance goal):
The moderation effect of the facet-specific change goal with the imagination change score (current-self) is not significantly different from zero, b = 0.032, p = 0.199.
3.8.2.30 Imagination - frequency of skill-building behaviors as moderator of change
Results summary (frequ = frequency of skill-building behavior):
The moderation effect of the frequency of skill-building behaviors with the imagination change score (ideal-self) is not significantly different from zero, b = 0.083, p = 0.198.
Results summary across the Big Five traits: trait-specific change goals (goals) and frequency of skill-building behaviors (frequency) as moderators on the latent change score
kable(df_table_hyp6[1:10, ], digits =3)
trait
moderator
estimate
std.all
statistic
p.value
extraversion
goals
0.093
0.122
0.881
0.378
extraversion
frequency
0.112
0.150
1.567
0.117
agreeableness
goals
0.036
0.116
1.173
0.241
agreeableness
frequency
0.105
0.265
2.990
0.003
conscientiousness
goals
-0.036
-0.093
-0.832
0.406
conscientiousness
frequency
-0.146
-0.219
-2.648
0.008
neuroticism
goals
-0.073
-0.165
-1.291
0.197
neuroticism
frequency
0.062
0.086
1.067
0.286
openness
goals
0.014
0.267
2.723
0.006
openness
frequency
0.010
0.227
2.068
0.039
Four moderator effects significantly differ from zero:
changes in current-level agreeableness are moderated by the frequency of skill-building behaviors
changes in current-level conscientiousness are moderated by the frequency of skill-building behaviors (but in the unexpected direction)
changes in current-level openness are moderated by the trait-specific change goals
changes in current-level openness are moderated by the frequency of skill-building behaviors
Results summary across the Big Five facets: trait-specific change goals (goals) and frequency of skill-building behaviors (frequency) as moderators on the latent change score
kable(df_table_hyp6[11:40, ], digits =3)
trait
moderator
estimate
std.all
statistic
p.value
sociability
goals
-0.006
-0.013
-0.163
0.871
sociability
frequency
0.051
0.071
0.776
0.438
assertiveness
goals
0.036
0.192
1.242
0.214
assertiveness
frequency
0.065
0.215
1.355
0.175
energy
goals
-0.002
-0.013
-0.143
0.886
energy
frequency
-0.060
-0.183
-1.495
0.135
compassion
goals
0.017
0.105
0.683
0.495
compassion
frequency
0.129
0.423
2.676
0.007
respectfulness
goals
0.037
0.151
1.474
0.141
respectfulness
frequency
0.088
0.193
2.117
0.034
trust
goals
-0.023
-0.084
-0.890
0.373
trust
frequency
-0.116
-0.236
-2.093
0.036
organization
goals
-0.027
-0.074
-0.689
0.491
organization
frequency
-0.130
-0.180
-2.023
0.043
productiveness
goals
-0.033
-0.118
-1.140
0.254
productiveness
frequency
-0.133
-0.256
-2.659
0.008
responsibility
goals
0.003
0.022
0.185
0.854
responsibility
frequency
0.027
0.093
0.780
0.435
anxiety
goals
-0.053
-0.148
-1.300
0.194
anxiety
frequency
0.069
0.091
0.905
0.365
depression
goals
-0.024
-0.105
-0.814
0.416
depression
frequency
0.020
0.039
0.438
0.661
volatility
goals
-0.030
-0.079
-0.900
0.368
volatility
frequency
-0.063
-0.090
-0.957
0.339
curiosity
goals
0.002
0.014
0.072
0.943
curiosity
frequency
0.097
0.394
1.865
0.062
aesthetic
goals
0.003
0.153
1.824
0.068
aesthetic
frequency
0.006
0.176
1.834
0.067
imagination
goals
0.032
0.113
1.284
0.199
imagination
frequency
0.083
0.147
1.288
0.198
Looking at the facets, we find five moderator effects that significantly differ from zero:
Within agreeableness, we find the effect for the frequency of skill-building behaviors from above represented in all the three facets, compassion, respectfulness, and trust.
The effect for conscientiousness is represented in two of the three facets, organization and productiveness.
However, the effect seen above for openness is mirrored in none of the facets.
3.9 Hypothesis 7: Desire to change and frequency of self-acceptance behaviors as moderators of change in personality in self-acceptance group
Desire to change and frequency of self-acceptance behaviors measured at the follow-up assessment will be positively related to change in ideal-self ratings in the self-acceptance group.
To test this hypothesis, we will estimate the mean-level difference in ideal trait ratings between baseline and follow up using a latent change model for each big five domain and facet. We will then include two moderators. The first will indicate how much the individual wanted to accept themselves on a given big five domain or facet. The second will indicate their frequency of self-acceptance behaviors. We will estimate the main effects of each of these variables and the interaction between these variables on the trait change score.
Reshape and split data set by intervention group:
Show the code
df_sbsa_wide_pers_sa_mod <- df_sbsa %>%filter(rando=="Self-Acceptance") %>%arrange(pid, time) %>%select(pid, time, starts_with(c("bf06", # only need ideal-level"sa07", # facet-specific acceptance goals"sa04"))) %>%# frequency self-acceptance behaviorspivot_wider(names_from = time,names_sep ="_t",values_from =c(starts_with(c("bf06", "sa07", "sa04")))) %>%select(-c(sa07_01_t2, sa07_02_t2, sa07_03_t2, sa07_04_t2, sa07_05_t2, sa07_06_t2, sa07_07_t2, sa07_08_t2, sa07_09_t2, sa07_10_t2, sa07_11_t2, sa07_12_t2, sa07_13_t2, sa07_14_t2, sa07_15_t2, sa04_01_t1, sa04_02_t1, sa04_03_t1)) # frequency of self-acceptance behaviors measured at T2colnames(df_sbsa_wide_pers_sa_mod)
3.9.1 Big Five traits
Run models for all traits with a template & loop:
Show the code
# create templates:# 1st, for facet-specific acceptance goalstrait_template_mod_goal_accept <-'trait_t1 =~ 1*ind01_t1 + lamb2*ind02_t1 + lamb3*ind03_t1 + lamb4*ind04_t1 + lamb5*ind05_t1 + lamb6*ind06_t1 + lamb7*ind07_t1 + lamb8*ind08_t1 + lamb9*ind09_t1 + lamb10*ind10_t1 + lamb11*ind11_t1 + lamb12*ind12_t1 # This specifies the measurement model for trait_t1 trait_t2 =~ 1*ind01_t2 + lamb2*ind02_t2 + lamb3*ind03_t2 + lamb4*ind04_t2 + lamb5*ind05_t2 + lamb6*ind06_t2 + lamb7*ind07_t2 + lamb8*ind08_t2 + lamb9*ind09_t2 + lamb10*ind10_t2 + lamb11*ind11_t2 + lamb12*ind12_t2 # This specifies the measurement model for trait_t2 with the equality constrained factor loadingsgoals =~ 1*ind_goal_1 + ind_goal_2 + ind_goal_3 # latent variable for moderatortrait_t2 ~ 1*trait_t1 # This parameter regresses trait_t2 perfectly on trait_t1d_trait_1 =~ 1*trait_t2 # This defines the latent change score factor as measured perfectly by scores on trait_t2trait_t2 ~ 0*1 # This line constrains the intercept of trait_t2 to 0trait_t2 ~~ 0*trait_t2 # This fixes the variance of trait_t2 to 0d_trait_1 ~ 1 # This estimates the intercept of the change score trait_t1 ~ 1 # This estimates the intercept of trait_t1 d_trait_1 ~~ d_trait_1 # This estimates the variance of the change scores trait_t1 ~~ trait_t1 # This estimates the variance of trait_t1 trait_t1 ~ goals # This estimates the moderation effect on personality at T1d_trait_1 ~ trait_t1 + goals # This estimates the self-feedback parameter and the moderation effect on the change scoregoals ~ 0*1 # This fixes the intercept of the moderator to 0goals ~~ goals # This estimates the variance of the moderatorind01_t1 ~~ ind01_t2 # This allows residual covariance on indicator X1 across T1 and T2ind02_t1 ~~ ind02_t2 # This allows residual covariance on indicator X2 across T1 and T2ind03_t1 ~~ ind03_t2 # This allows residual covariance on indicator X3 across T1 and T2ind04_t1 ~~ ind04_t2 # This allows residual covariance on indicator X4 across T1 and T2ind05_t1 ~~ ind05_t2 # This allows residual covariance on indicator X5 across T1 and T2ind06_t1 ~~ ind06_t2 # This allows residual covariance on indicator X6 across T1 and T2ind07_t1 ~~ ind07_t2 # This allows residual covariance on indicator X7 across T1 and T2ind08_t1 ~~ ind08_t2 # This allows residual covariance on indicator X8 across T1 and T2ind09_t1 ~~ ind09_t2 # This allows residual covariance on indicator X9 across T1 and T2ind10_t1 ~~ ind10_t2 # This allows residual covariance on indicator X10 across T1 and T2ind11_t1 ~~ ind11_t2 # This allows residual covariance on indicator X11 across T1 and T2ind12_t1 ~~ ind12_t2 # This allows residual covariance on indicator X12 across T1 and T2ind01_t1 ~~ res1*ind01_t1 # This allows residual variance on indicator X1 at T1 ind02_t1 ~~ res2*ind02_t1 # This allows residual variance on indicator X2 at T1ind03_t1 ~~ res3*ind03_t1 # This allows residual variance on indicator X3 at T1ind04_t1 ~~ res4*ind04_t1 # This allows residual variance on indicator X4 at T1ind05_t1 ~~ res5*ind05_t1 # This allows residual variance on indicator X5 at T1ind06_t1 ~~ res6*ind06_t1 # This allows residual variance on indicator X6 at T1 ind07_t1 ~~ res7*ind07_t1 # This allows residual variance on indicator X7 at T1ind08_t1 ~~ res8*ind08_t1 # This allows residual variance on indicator X8 at T1ind09_t1 ~~ res9*ind09_t1 # This allows residual variance on indicator X9 at T1ind10_t1 ~~ res10*ind10_t1 # This allows residual variance on indicator X10 at T1ind11_t1 ~~ res11*ind11_t1 # This allows residual variance on indicator X11 at T1ind12_t1 ~~ res12*ind12_t1 # This allows residual variance on indicator X12 at T1ind01_t2 ~~ res1*ind01_t2 # This allows residual variance on indicator X1 at T2 ind02_t2 ~~ res2*ind02_t2 # This allows residual variance on indicator X2 at T2 ind03_t2 ~~ res3*ind03_t2 # This allows residual variance on indicator X3 at T2ind04_t2 ~~ res4*ind04_t2 # This allows residual variance on indicator X4 at T2ind05_t2 ~~ res5*ind05_t2 # This allows residual variance on indicator X5 at T2ind06_t2 ~~ res6*ind06_t2 # This allows residual variance on indicator X6 at T2 ind07_t2 ~~ res7*ind07_t2 # This allows residual variance on indicator X7 at T2 ind08_t2 ~~ res8*ind08_t2 # This allows residual variance on indicator X8 at T2ind09_t2 ~~ res9*ind09_t2 # This allows residual variance on indicator X9 at T2ind10_t2 ~~ res10*ind10_t2 # This allows residual variance on indicator X10 at T2ind11_t2 ~~ res11*ind11_t2 # This allows residual variance on indicator X11 at T2ind12_t2 ~~ res12*ind12_t2 # This allows residual variance on indicator X12 at T2ind01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind02_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind03_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind04_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind05_t1 ~ m5*1 # This estimates the intercept of X5 at T1ind06_t1 ~ m6*1 # This estimates the intercept of X6 at T1ind07_t1 ~ m7*1 # This estimates the intercept of X7 at T1ind08_t1 ~ m8*1 # This estimates the intercept of X8 at T1ind09_t1 ~ m9*1 # This estimates the intercept of X9 at T1ind10_t1 ~ m10*1 # This estimates the intercept of X10 at T1ind11_t1 ~ m11*1 # This estimates the intercept of X11 at T1ind12_t1 ~ m12*1 # This estimates the intercept of X12 at T1ind01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind02_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind03_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind04_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind05_t2 ~ m5*1 # This estimates the intercept of X5 at T2ind06_t2 ~ m6*1 # This estimates the intercept of X6 at T2ind07_t2 ~ m7*1 # This estimates the intercept of X7 at T2ind08_t2 ~ m8*1 # This estimates the intercept of X8 at T2ind09_t2 ~ m9*1 # This estimates the intercept of X9 at T2ind10_t2 ~ m10*1 # This estimates the intercept of X10 at T2ind11_t2 ~ m11*1 # This estimates the intercept of X11 at T2ind12_t2 ~ m12*1 # This estimates the intercept of X12 at T2ind_goal_1 ~~ ind_goal_1ind_goal_2 ~~ ind_goal_2ind_goal_3 ~~ ind_goal_3ind_goal_1 ~ 1ind_goal_2 ~ 1ind_goal_3 ~ 1'trait_facets_nrs <-list(a1 =c(1:3), b2 =c(4:6), c3 =c(7:9), d4 =c(10:12), e5 =c(13:15)) # matching facet nrs to traits # loop across 5 traitsfor (i in1:5) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post ideal (6 = ideal) items =paste0(bfi_versions[[6]], item_nrs) mod_names =paste0("sa07_", str_pad(trait_facets_nrs[[i]], 2, pad ="0"), "_t1") template_filled <-str_replace_all(trait_template_mod_goal_accept, c("trait"= short_name,"ind01"= items[1], "ind02"= items[2], "ind03"= items[3], "ind04"= items[4],"ind05"= items[5], "ind06"= items[6], "ind07"= items[7], "ind08"= items[8],"ind09"= items[9], "ind10"= items[10], "ind11"= items[11], "ind12"= items[12],"ind_goal_1"= mod_names[1], "ind_goal_2"= mod_names[2], "ind_goal_3"= mod_names[3])) trait_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sa_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_specif_hyp7")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_specif_hyp7")), trait_model_fit))} # 2nd, for frequency of self-acceptance behaviortrait_template_mod_frequ_accept <-'trait_t1 =~ 1*ind01_t1 + lamb2*ind02_t1 + lamb3*ind03_t1 + lamb4*ind04_t1 + lamb5*ind05_t1 + lamb6*ind06_t1 + lamb7*ind07_t1 + lamb8*ind08_t1 + lamb9*ind09_t1 + lamb10*ind10_t1 + lamb11*ind11_t1 + lamb12*ind12_t1 # This specifies the measurement model for extra_t1 trait_t2 =~ 1*ind01_t2 + lamb2*ind02_t2 + lamb3*ind03_t2 + lamb4*ind04_t2 + lamb5*ind05_t2 + lamb6*ind06_t2 + lamb7*ind07_t2 + lamb8*ind08_t2 + lamb9*ind09_t2 + lamb10*ind10_t2 + lamb11*ind11_t2 + lamb12*ind12_t2 # This specifies the measurement model for extra_t2 with the equality constrained factor loadingsfrequ =~ 1*sa04_01_t2 + sa04_02_t2 + sa04_03_t2 # latent variable for moderatortrait_t2 ~ 1*trait_t1 # This parameter regresses trait_t2 perfectly on trait_t1d_trait_1 =~ 1*trait_t2 # This defines the latent change score factor as measured perfectly by scores on trait_t2trait_t2 ~ 0*1 # This line constrains the intercept of trait_t2 to 0trait_t2 ~~ 0*trait_t2 # This fixes the variance of trait_t2 to 0d_trait_1 ~ 1 # This estimates the intercept of the change score trait_t1 ~ 1 # This estimates the intercept of trait_t1 d_trait_1 ~~ d_trait_1 # This estimates the variance of the change scores trait_t1 ~~ trait_t1 # This estimates the variance of trait_t1 trait_t1 ~ frequ # This estimates the moderation effect on personality at T1d_trait_1 ~ trait_t1 + frequ # This estimates the self-feedback parameter and the moderation effect on the change scorefrequ ~ 0*1 # This fixes the intercept of the moderator to 0frequ ~~ frequ # This estimates the variance of the moderatorind01_t1 ~~ ind01_t2 # This allows residual covariance on indicator X1 across T1 and T2ind02_t1 ~~ ind02_t2 # This allows residual covariance on indicator X2 across T1 and T2ind03_t1 ~~ ind03_t2 # This allows residual covariance on indicator X3 across T1 and T2ind04_t1 ~~ ind04_t2 # This allows residual covariance on indicator X4 across T1 and T2ind05_t1 ~~ ind05_t2 # This allows residual covariance on indicator X5 across T1 and T2ind06_t1 ~~ ind06_t2 # This allows residual covariance on indicator X6 across T1 and T2ind07_t1 ~~ ind07_t2 # This allows residual covariance on indicator X7 across T1 and T2ind08_t1 ~~ ind08_t2 # This allows residual covariance on indicator X8 across T1 and T2ind09_t1 ~~ ind09_t2 # This allows residual covariance on indicator X9 across T1 and T2ind10_t1 ~~ ind10_t2 # This allows residual covariance on indicator X10 across T1 and T2ind11_t1 ~~ ind11_t2 # This allows residual covariance on indicator X11 across T1 and T2ind12_t1 ~~ ind12_t2 # This allows residual covariance on indicator X12 across T1 and T2ind01_t1 ~~ res1*ind01_t1 # This allows residual variance on indicator X1 at T1 ind02_t1 ~~ res2*ind02_t1 # This allows residual variance on indicator X2 at T1ind03_t1 ~~ res3*ind03_t1 # This allows residual variance on indicator X3 at T1ind04_t1 ~~ res4*ind04_t1 # This allows residual variance on indicator X4 at T1ind05_t1 ~~ res5*ind05_t1 # This allows residual variance on indicator X5 at T1ind06_t1 ~~ res6*ind06_t1 # This allows residual variance on indicator X6 at T1 ind07_t1 ~~ res7*ind07_t1 # This allows residual variance on indicator X7 at T1ind08_t1 ~~ res8*ind08_t1 # This allows residual variance on indicator X8 at T1ind09_t1 ~~ res9*ind09_t1 # This allows residual variance on indicator X9 at T1ind10_t1 ~~ res10*ind10_t1 # This allows residual variance on indicator X10 at T1ind11_t1 ~~ res11*ind11_t1 # This allows residual variance on indicator X11 at T1ind12_t1 ~~ res12*ind12_t1 # This allows residual variance on indicator X12 at T1ind01_t2 ~~ res1*ind01_t2 # This allows residual variance on indicator X1 at T2 ind02_t2 ~~ res2*ind02_t2 # This allows residual variance on indicator X2 at T2 ind03_t2 ~~ res3*ind03_t2 # This allows residual variance on indicator X3 at T2ind04_t2 ~~ res4*ind04_t2 # This allows residual variance on indicator X4 at T2ind05_t2 ~~ res5*ind05_t2 # This allows residual variance on indicator X5 at T2ind06_t2 ~~ res6*ind06_t2 # This allows residual variance on indicator X6 at T2 ind07_t2 ~~ res7*ind07_t2 # This allows residual variance on indicator X7 at T2 ind08_t2 ~~ res8*ind08_t2 # This allows residual variance on indicator X8 at T2ind09_t2 ~~ res9*ind09_t2 # This allows residual variance on indicator X9 at T2ind10_t2 ~~ res10*ind10_t2 # This allows residual variance on indicator X10 at T2ind11_t2 ~~ res11*ind11_t2 # This allows residual variance on indicator X11 at T2ind12_t2 ~~ res12*ind12_t2 # This allows residual variance on indicator X12 at T2ind01_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind02_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind03_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind04_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind05_t1 ~ m5*1 # This estimates the intercept of X5 at T1ind06_t1 ~ m6*1 # This estimates the intercept of X6 at T1ind07_t1 ~ m7*1 # This estimates the intercept of X7 at T1ind08_t1 ~ m8*1 # This estimates the intercept of X8 at T1ind09_t1 ~ m9*1 # This estimates the intercept of X9 at T1ind10_t1 ~ m10*1 # This estimates the intercept of X10 at T1ind11_t1 ~ m11*1 # This estimates the intercept of X11 at T1ind12_t1 ~ m12*1 # This estimates the intercept of X12 at T1ind01_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind02_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind03_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind04_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind05_t2 ~ m5*1 # This estimates the intercept of X5 at T2ind06_t2 ~ m6*1 # This estimates the intercept of X6 at T2ind07_t2 ~ m7*1 # This estimates the intercept of X7 at T2ind08_t2 ~ m8*1 # This estimates the intercept of X8 at T2ind09_t2 ~ m9*1 # This estimates the intercept of X9 at T2ind10_t2 ~ m10*1 # This estimates the intercept of X10 at T2ind11_t2 ~ m11*1 # This estimates the intercept of X11 at T2ind12_t2 ~ m12*1 # This estimates the intercept of X12 at T2sa04_01_t2 ~~ sa04_01_t2sa04_02_t2 ~~ sa04_02_t2sa04_03_t2 ~~ sa04_03_t2sa04_01_t2 ~ 1sa04_02_t2 ~ 1sa04_03_t2 ~ 1'# loop across 5 traitsfor (i in1:5) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post ideal items =paste0(bfi_versions[[6]], item_nrs) template_filled <-str_replace_all(trait_template_mod_frequ_accept, c("trait"= short_name,"ind01"= items[1], "ind02"= items[2], "ind03"= items[3], "ind04"= items[4],"ind05"= items[5], "ind06"= items[6], "ind07"= items[7], "ind08"= items[8],"ind09"= items[9], "ind10"= items[10], "ind11"= items[11], "ind12"= items[12])) trait_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sa_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_frequ_hyp7")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_frequ_hyp7")), trait_model_fit))}
3.9.1.1 Extraversion: specific, facet-level acceptance goals as moderator of change
Results summary (goals = trait/facet specific acceptance goal):
The moderation effect of specific, facet-level acceptance goals with the extraversion change score (ideal-self) is not significantly different from zero, b = -0.035, p = 0.267.
3.9.1.2 Extraversion: frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of specific, facet-level acceptance goals with the agreeableness change score (ideal-self) is not significantly different from zero, b = -0.012, p = 0.756.
3.9.1.4 Agreeableness: frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of specific, facet-level acceptance goals with the conscientiousness change score (ideal-self) is not significantly different from zero, b = 0.023, p = 0.229.
3.9.1.6 Conscientiousness: frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The frequency of self-acceptance behaviors significantly moderates changes in conscientiousness (ideal-self), b = -0.082, p = 0.014, although in an unexpected direction such that more frequent self-acceptance behaviors are associated with more pronounced decreases in conscientiousness.
3.9.1.7 Neuroticism: specific, facet-level acceptance goals as moderator of change
Results summary (goals = trait/facet specific acceptance goal):
The moderation effect of the frequency of self-acceptance behaviors with the neuroticism change score (ideal-self) is not significantly different from zero, b = 0.049, p = 0.076.
3.9.1.9 Openness: specific, facet-level acceptance goals as moderator of change
Results summary (goals = trait/facet specific acceptance goal):
The moderation effect of specific, facet-level acceptance goals with the openness change score (ideal-self) is not significantly different from zero, b = -0.001, p = NA. (… model did not converge properly!)
3.9.1.10 Openness: frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of skill building behavior):
The moderation effect of frequency of self-acceptance behaviors with the openness change score (ideal-self) is not significantly different from zero, b = 0.003, p = NA. (… model did not converge properly!)
3.9.2 Big Five facets
Run models for all facets with a template & loop:
Show the code
# create templates:# 1st, for facet-specific acceptance goalfacet_template_mod_goal_accept <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)facet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 facet_t1 ~ ind_goal # This estimates the moderation effect on personality at T1d_facet_1 ~ facet_t1 + ind_goal # This estimates the self-feedback parameter and the moderation effect on the change scoreind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2ind_goal ~~ ind_goalind_goal ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post ideal items =paste0(bfi_versions[[6]], item_nrs) mod_name =paste0("sa07_", str_pad(i-5, 2, pad ="0"), "_t1") template_filled <-str_replace_all(facet_template_mod_goal_accept, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4],"ind_goal"= mod_name)) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sa_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_specif_hyp7")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_specif_hyp7")), facet_model_fit))} # 2nd, for frequency of self-acceptance behaviorfacet_template_mod_frequ_accept <-'facet_t1 =~ 1*ind1_t1 + lamb2*ind2_t1 + lamb3*ind3_t1 + lamb4*ind4_t1 # This specifies the measurement model for facet at T1facet_t2 =~ 1*ind1_t2 + lamb2*ind2_t2 + lamb3*ind3_t2 + lamb4*ind4_t2 # This specifies the measurement model for facet at T2 (with equality constraints)frequ =~ 1*sa04_01_t2 + sa04_02_t2 + sa04_03_t2 # latent variable for moderatorfacet_t2 ~ 1*facet_t1 # This parameter regresses facet_t2 perfectly on facet_t1d_facet_1 =~ 1*facet_t2 # This defines the latent change score factor as measured perfectly by scores on facet_t2facet_t2 ~ 0*1 # This line constrains the intercept of facet_t2 to 0facet_t2 ~~ 0*facet_t2 # This fixes the variance of facet_t2 to 0d_facet_1 ~ 1 # This estimates the intercept of the change score facet_t1 ~ 1 # This estimates the intercept of facet_t1 d_facet_1 ~~ d_facet_1 # This estimates the variance of the change scores facet_t1 ~~ facet_t1 # This estimates the variance of facet_t1 facet_t1 ~ frequ # This estimates the moderation effect on personality at T1d_facet_1 ~ facet_t1 + frequ # This estimates the self-feedback parameter and the moderation effect on the change scorefrequ ~ 0*1 # This fixes the intercept of the moderator to 0frequ ~~ frequ # This estimates the variance of the moderatorind1_t1 ~~ ind1_t2 # This allows residual covariance on indicator X1 across T1 and T2ind2_t1 ~~ ind2_t2 # This allows residual covariance on indicator X2 across T1 and T2ind3_t1 ~~ ind3_t2 # This allows residual covariance on indicator X3 across T1 and T2ind4_t1 ~~ ind4_t2 # This allows residual covariance on indicator X4 across T1 and T2ind1_t1 ~~ res1*ind1_t1 # This allows residual variance on indicator X1 at T1 ind2_t1 ~~ res2*ind2_t1 # This allows residual variance on indicator X2 at T1ind3_t1 ~~ res3*ind3_t1 # This allows residual variance on indicator X3 at T1ind4_t1 ~~ res4*ind4_t1 # This allows residual variance on indicator X4 at T1ind1_t2 ~~ res1*ind1_t2 # This allows residual variance on indicator X1 at T2 ind2_t2 ~~ res2*ind2_t2 # This allows residual variance on indicator X2 at T2 ind3_t2 ~~ res3*ind3_t2 # This allows residual variance on indicator X3 at T2ind4_t2 ~~ res4*ind4_t2 # This allows residual variance on indicator X4 at T2ind1_t1 ~ 0*1 # This constrains the intercept of X1 to 0 at T1ind2_t1 ~ m2*1 # This estimates the intercept of X2 at T1ind3_t1 ~ m3*1 # This estimates the intercept of X3 at T1ind4_t1 ~ m4*1 # This estimates the intercept of X4 at T1ind1_t2 ~ 0*1 # This constrains the intercept of X1 to 0 at T2ind2_t2 ~ m2*1 # This estimates the intercept of X2 at T2ind3_t2 ~ m3*1 # This estimates the intercept of X3 at T2ind4_t2 ~ m4*1 # This estimates the intercept of X4 at T2sa04_01_t2 ~~ sa04_01_t2sa04_02_t2 ~~ sa04_02_t2sa04_03_t2 ~~ sa04_03_t2sa04_01_t2 ~ 1sa04_02_t2 ~ 1sa04_03_t2 ~ 1'# loop across 15 facetsfor (i in6:length(b5_vars)) { item_nrs = b5_vars[[i]][[1]] short_name =str_trunc(names(b5_vars)[i], 5, ellipsis ="")# use BFI version combined pre&post ideal items =paste0(bfi_versions[[6]], item_nrs) template_filled <-str_replace_all(facet_template_mod_frequ_accept, c("facet"= short_name,"ind1"= items[1], "ind2"= items[2], "ind3"= items[3], "ind4"= items[4])) facet_model_fit <-lavaan(template_filled, data=df_sbsa_wide_pers_sa_mod, estimator='mlr', fixed.x=FALSE, missing='fiml')eval(call("<-", as.name(paste0("mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_frequ_hyp7")), template_filled))eval(call("<-", as.name(paste0("fit_mi_lcs_", short_name, "_", str_sub(names(bfi_versions)[6], 6), "_frequ_hyp7")), facet_model_fit))}
3.9.2.1 Sociability - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the sociability change score (ideal-self) is not significantly different from zero, b = -0.031, p = 0.231.
3.9.2.2 Sociability - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with sociability change score (ideal-self) is not significantly different from zero, b = 0.005, p = 0.88.
3.9.2.3 Assertiveness - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the assertiveness change score (ideal-self) is not significantly different from zero, b = -0.013, p = 0.318.
3.9.2.4 Assertiveness - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the assertiveness change score (ideal-self) is not significantly different from zero, b = 0.059, p = 0.067.
3.9.2.5 Energy - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the energy change score (ideal-self) is not significantly different from zero, b = 0.013, p = 0.272.
3.9.2.6 Energy - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the energy change score (ideal-self) is not significantly different from zero, b = -0.03, p = 0.275.
3.9.2.7 Compassion - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the compassion change score (ideal-self) is not significantly different from zero, b = -0.034, p = 0.251.
3.9.2.8 Compassion - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the compassion change score (ideal-self) is not significantly different from zero, b = -0.019, p = 0.809.
3.9.2.9 Respectfulness - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the respectfulness change score (ideal-self) is not significantly different from zero, b = -0.005, p = 0.789.
3.9.2.10 Respectfulness - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the respectfulness change score (ideal-self) is not significantly different from zero, b = 0.036, p = 0.316.
3.9.2.11 Trust - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the trust change score (ideal-self) is not significantly different from zero, b = 0.02, p = 0.287.
3.9.2.12 Trust - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the trust change score (ideal-self) is not significantly different from zero, b = -0.078, p = 0.09.
3.9.2.13 Organization - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the organization change score (ideal-self) is not significantly different from zero, b = 0.014, p = 0.363.
3.9.2.14 Organization - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the facet-specific acceptance goal with the productiveness change score (ideal-self) is not significantly different from zero, b = 0.002, p = 0.918.
3.9.2.16 Productiveness - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the productiveness change score (ideal-self) is not significantly different from zero, b = -0.07, p = 0.056.
3.9.2.17 Responsibility - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the responsibility change score (ideal-self) is not significantly different from zero, b = -0.018, p = 0.442.
3.9.2.18 Responsibility - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the responsibility change score (ideal-self) is not significantly different from zero, b = 0.075, p = 0.168.
3.9.2.19 Anxiety - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the anxiety change score (ideal-self) is not significantly different from zero, b = -0.005, p = 0.843.
3.9.2.20 Anxiety - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the anxiety change score (ideal-self) is not significantly different from zero, b = 0.037, p = 0.523.
3.9.2.21 Depression - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the depression change score (ideal-self) is not significantly different from zero, b = -0.005, p = 0.666.
3.9.2.22 Depression - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the depression change score (ideal-self) is not significantly different from zero, b = 0.035, p = 0.156.
3.9.2.23 Volatility - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the volatility change score (ideal-self) is not significantly different from zero, b = -0.005, p = 0.848.
3.9.2.24 Volatility - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the volatility change score (ideal-self) is significantly different from zero, b = -0.087, p = 0.079.
3.9.2.25 Curiosity - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the curiosity change score (ideal-self) is not significantly different from zero, b = -0.023, p = 0.241.
3.9.2.26 Curiosity - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the curiosity change score (ideal-self) is not significantly different from zero, b = 0.02, p = 0.616.
3.9.2.27 Aesthetic - specific, facet-level acceptance goal as moderator of change
Results summary (sa07_xx_t1 = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the aesthetic change score (ideal-self) is not significantly different from zero, b = -0.003, p = 0.452.
3.9.2.28 Aesthetic - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the aesthetic change score (ideal-self) is not significantly different from zero, b = 0.012, p = 0.398.
3.9.2.29 Imagination - specific, facet-level acceptance goal as moderator of change
Results summary (*sa07_$$_t1* = trait/facet specific acceptance goal):
The moderation effect of the facet-specific acceptance goal with the imagination change score (ideal-self) is not significantly different from zero, b = 0.01, p = 0.576.
3.9.2.30 Imagination - frequency of self-acceptance behaviors as moderator of change
Results summary (frequ = frequency of self-acceptance behavior):
The moderation effect of the frequency of self-acceptance behaviors with the imagination change score (ideal-self) is not significantly different from zero, b = -0.003, p = 0.945.
Results summary across the Big Five traits: trait-specific acceptance goals (goals) and frequency of self-acceptance behaviors (frequency) as moderators on the latent change score
kable(df_table_hyp7[1:10, ], digits =3)
trait
moderator
estimate
std.all
statistic
p.value
extraversion
goals
-0.035
-0.124
-1.110
0.267
extraversion
frequency
0.054
0.178
1.977
0.048
agreeableness
goals
-0.012
-0.027
-0.310
0.756
agreeableness
frequency
0.077
0.161
1.800
0.072
conscientiousness
goals
0.023
0.095
1.203
0.229
conscientiousness
frequency
-0.082
-0.236
-2.456
0.014
neuroticism
goals
-0.062
-0.204
-2.185
0.029
neuroticism
frequency
0.049
0.151
1.774
0.076
openness
goals
-0.001
-0.036
NA
NA
openness
frequency
0.003
0.160
NA
NA
Four moderator effects significantly differ from zero:
changes in ideal-level extraversion are moderated by the frequency of self-acceptance behaviors
changes in ideal-level conscientiousness are moderated by the frequency of self-acceptance behaviors (but in the unexpected direction)
changes in ideal-level neuroticism are moderated by the trait-/facet-level specific acceptance goals
models for openness did not converge (?)
Results summary across the Big Five facets: trait-specific acceptance goals (goals) and frequency of self-acceptance behaviors (frequency) as moderators on the latent change score
kable(df_table_hyp7[11:40, ], digits =3)
trait
moderator
estimate
std.all
statistic
p.value
sociability
goals
-0.031
-0.153
-1.197
0.231
sociability
frequency
0.005
0.015
0.151
0.880
assertiveness
goals
-0.013
-0.089
-0.998
0.318
assertiveness
frequency
0.059
0.213
1.834
0.067
energy
goals
0.013
0.142
1.098
0.272
energy
frequency
-0.030
-0.173
-1.092
0.275
compassion
goals
-0.034
-0.115
-1.147
0.251
compassion
frequency
-0.019
-0.037
-0.242
0.809
respectfulness
goals
-0.005
-0.026
-0.268
0.789
respectfulness
frequency
0.036
0.120
1.003
0.316
trust
goals
0.020
0.098
1.064
0.287
trust
frequency
-0.078
-0.211
-1.695
0.090
organization
goals
0.014
0.082
0.910
0.363
organization
frequency
-0.100
-0.331
-2.504
0.012
productiveness
goals
0.002
0.009
0.102
0.918
productiveness
frequency
-0.070
-0.230
-1.910
0.056
responsibility
goals
-0.018
-0.067
-0.769
0.442
responsibility
frequency
0.075
0.149
1.378
0.168
anxiety
goals
-0.005
-0.024
-0.199
0.843
anxiety
frequency
0.037
0.088
0.638
0.523
depression
goals
-0.005
-0.052
-0.432
0.666
depression
frequency
0.035
0.175
1.418
0.156
volatility
goals
-0.005
-0.016
-0.192
0.848
volatility
frequency
-0.087
-0.186
-1.754
0.079
curiosity
goals
-0.023
-0.142
-1.172
0.241
curiosity
frequency
0.020
0.069
0.501
0.616
aesthetic
goals
-0.003
-0.099
-0.753
0.452
aesthetic
frequency
0.012
0.199
0.845
0.398
imagination
goals
0.010
0.053
0.559
0.576
imagination
frequency
-0.003
-0.009
-0.069
0.945
Looking at the facets, we find five moderator effects that significantly differ from zero:
The effect for conscientiousness is only represented within the organization facet.
No other significant effects.
4 Exploratory results
4.1 a) Differences in change across experimental groups
We will explore a) whether change in psychological well-being indicators as well as the difference between real- and ideal- self will differ across groups at follow-up.
4.2 b) Personal project dimensions
We will explore b) whether extent of change/acceptance is related to personal project dimension variables.
4.3 c) Traits that were selected as change goals
We will explore c) whether there are stronger rates of change/acceptance on traits that were selected as change goals than those that were not.